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School of Design and the Built Environment
A Hybrid OSM–BIM Framework for Construction Management
System
Pejman Ghasemi Poor Sabet
19234296
This thesis is presented for the Degree of Doctor of Philosophy of Curtin University
June 2020
i
Declaration
To the best of my knowledge and belief, this thesis contains no material
previously published by any other person except where due acknowledgement has been
made. This thesis contains no material which has been accepted for the award of any
other degree or diploma in any university.
The research presented and reported in this thesis was conducted in accordance
with the National Health and Medical Research Council National Statement on Ethical
Conduct in Human Research (2007) – updated March 2014. The proposed research
study received human research ethics approval from the Curtin University Human
Research Ethics Committee (EC00262), Approval Number #HRE2019-0070.
This thesis has been structured according to the requirements of a hybrid thesis
determined by Curtin University
Signature:
Date: 25-06-2020
ii
Abstract
Building information modelling (BIM) and off-site manufacturing (OSM) are
advanced techniques, which emerged to promote project performance through the
improvement of key productivity indicators (KPrIs). In theory, BIM and OSM optimise
performance aspects, including time, cost, quality, safety and stockholders’ satisfaction.
However, reports have not yet confirmed that BIM and OSM have fulfilled the
objectives set out for their overall project performance. The overall project performance
is subject to the improvement of construction productivity. These techniques may
require the help of some more productivity fundamentals, in addition to their own
capabilities. Therefore, this research developed the interactions between OSM and BIM
and determined the influence of OSM–BIM interactions to maximize overall project
performance. Extensive literature review and relevant analysis techniques were adopted
to obtain a comprehensive understanding for the development of a hybrid OSM–BIM
system. This research had four objectives. The first objective required an all-embracing
review of poor productivity roots in construction projects, to identify a range of
productivity fundamentals that support the capabilities of the most common and
advanced techniques. Then the research was narrowed in scope to focus on BIM
application in OSM-based projects. The second objective was to formulate an insightful,
interactive picture of the influential standalone capabilities of each technique, for a
hybrid, OSM–BIM conceptual framework contributing to the project performance. The
third objective was to identify KPrIs and investigate the capabilities of OSM and BIM
techniques in detail—as well as their potential interactions for productivity
improvement. The fourth objective was to determine the influences of OSM–BIM
interactions on overall project performance, using an in-depth, complex evaluation of
the practicality of the interactions. Structural equation modelling (SEM) was adopted to
iii
examine the complex relationships among variables in data acquired via a questionnaire
survey. Twelve OSM–BIM interactions were developed and evaluated from the
perspective of productivity improvement. The findings showed that BIM and OSM had
no significant influence on overall project performance in Australia when applied
individually. However, BIM had a significant influence on OSM, meaning that the
capabilities of the two techniques were interactive. Further, OSM–BIM interactions had
a significant influence on overall project performance. From a theoretical perspective,
the technical details that delivered these interactions provide new insights into removing
inefficiencies in OSM-based projects via BIM application. The outcome of this research
is aligned with the diffusion of innovation theory in the construction industry because it
has clarified three essential elements of innovation: idea generation, opportunities, and
diffusion.
iv
Acknowledgements
Thank you to my main supervisor, Associate Professor Heap-Yih (John) Chong
for his inspiration and continuous guidance. I am also thankful to my co-supervisor, Dr
Chamila Ramanayaka for his encouragement and support. I am grateful to all the
professors, associate professors, doctors and lecturers for motivating me on various
occasions. I thank Engineers Australia for its valuable cooperation. I appreciate all the
respondents for their participation in the survey. I am also grateful to Curtin University,
particularly the staff in the School of Design and the Built and Environment, BIM
Research Centre and Graduate Research School, for providing me with all the necessary
facilities required to conduct my research.
I cannot thank my parents, my uncle, Professor Ardeshir Tahmasebi and his
beloved wife, my brother, Dr Peyman Sabet and his beloved wife, my sister, and my
partner enough for their massive ongoing support. They were the driving force behind
the success of my Ph.D. research. Without their inspiration, drive and support which
made me understand the value of education, I would not be able to achieve the
milestones in my life.
v
List of Publications Included as Part of the Thesis
Sabet, P., Chong, H.Y. & Ramanayaka, C.D.D. (2020). Appraisal of interactions
between building information modelling and off-site manufacturing for project
performance. Submitted to ASCE journals (under review).
Sabet, P., & Chong, H.Y. (2020). Pathways for the Improvement of
Construction Productivity: A Perspective on the Adoption of Advanced Techniques.
Advances in Civil Engineering, Vol. 2020. https://doi.org/10.1155/2020/5170759
Sabet, P. & Chong, H. Y (2019). Interactions between building information
modelling and off-site manufacturing for productivity improvement. International
Journal of Managing Projects in Business, Vol. 13 No. 2, pp. 233-255.
https://doi.org/10.1108/IJMPB-08-2018-0168
Sabet, P., & Chong, H.Y. (2018). A conceptual hybrid OSM-BIM framework to
improve construction project performance. Educating Building Professionals for the
Future in the Globalised World, Singapore, pp. 204-213, September 26-28.
vi
I warrant that I have obtained, where necessary, permission from the copyright
owners to use any third party copyright material reproduced in the thesis (e.g.
questionnaires, artwork, unpublished letters), or to use any of my own published work
(e.g. journal articles) in which the copyright is held by another party (e.g. publisher, co-
author).
Copies of the permission statements are included in Appendix B-C.
vii
Statement of Author’s Contributions
Co-author statements declaring and endorsing the candidate’s contributions to each
paper included in this thesis can be found in Appendix F-J.
viii
Table of Contents
Declaration ........................................................................................................................ i
Abstract ............................................................................................................................ ii
Acknowledgements ......................................................................................................... iv
List of Publications Included as Part of the Thesis ...................................................... v
Statement of Author’s Contributions .......................................................................... vii
Table of Contents ......................................................................................................... viii
List of Tables .................................................................................................................. xi
List of Figures ................................................................................................................ xii
Glossary of Terms ........................................................................................................ xiii
Chapter 1: Introduction ................................................................................................. 1 1.1 Introduction ............................................................................................................. 1
1.2 Research Background and Aim of the research ...................................................... 1 1.2.1 The need for productivity improvement. ......................................................... 2 1.2.2 Value-making approaches (VmAs). ................................................................. 4
1.2.3 Total quality management and Deming cycle. ................................................. 4 1.2.4 Statement of the problem and research gap ..................................................... 5
1.2.5 The idea of BIM in OSM ................................................................................. 6 1.3 Exegesis of Thesis Structure ................................................................................... 8
1.3.1 Pathways for the improvement of construction productivity: A
perspective on the adoption of advanced techniques. ...................................... 8
1.3.2 The current influential standalone capabilities of BIM and OSM for a
hybrid OSM–BIM conceptual framework. .................................................... 10 1.3.3 The identification of potential interactions between BIM and OSM for
productivity improvement. ............................................................................ 11 1.3.4 The influences of interactions between BIM and OSM on project
performance via productivity improvement. ................................................. 12 1.4 Summary ............................................................................................................... 13
Chapter 2: Research Methodology .............................................................................. 15
2.1 Research ................................................................................................................ 15 2.2 Inductive Approach ............................................................................................... 15
2.3 Types of Research Methodologies ........................................................................ 16 2.3.1 Quantitative methodology. ............................................................................. 16
2.4 The research methodology of this study ............................................................... 17 2.4.1 The research methodology to meet the first and the second objectives. ........ 17 2.4.2 The research methodology to meet the third objective. ................................. 18 2.4.3 The research methodology to meet the fourth objective. ............................... 19
2.5 Summary ............................................................................................................... 21
Chapter 3: Pathways for the Improvement of Construction Productivity: A
Perspective on the Adoption of Advanced Techniques .............................................. 24
Abstract .......................................................................................................................... 24 3.1 Introduction ........................................................................................................... 25 3.2 Literature Review .................................................................................................. 26
ix
3.2.1 Productivity requirements and issues. ............................................................ 26
3.2.2 The debate on ROI. ........................................................................................ 30
3.2.3 Emerging advanced techniques for construction projects. ............................. 31 3.2.4 Productivity indicators. .................................................................................. 39
3.3 Methodology ......................................................................................................... 40 3.4 Findings and Data Analysis .................................................................................. 47 3.5 Integrated Framework ........................................................................................... 52
3.6 Discussion and Conclusion ................................................................................... 55 3.7 Limitations of the Research .................................................................................. 57
Chapter 4: A Conceptual Hybrid OSM–BIM Framework to Improve
Construction Project Performance .............................................................................. 58
Abstract .......................................................................................................................... 58
4.1 Introduction ........................................................................................................... 60
4.2 Scoping Review .................................................................................................... 61 4.3 Background ........................................................................................................... 62
4.3.1 Project performance variables. ....................................................................... 62 4.3.2 OSM. .............................................................................................................. 65 4.3.3 BIM. ............................................................................................................... 70 4.3.4 Barriers for the development of the hybrid OSM–BIM system. .................... 75
4.4 Discussion ............................................................................................................. 76 4.5 Conclusion and Further Research ......................................................................... 78
Chapter 5: Potential Interactions Between Building Information Modelling
and Off-Site Manufacturing for Productivity Improvement .................................... 80
Abstract .......................................................................................................................... 80
5.1 Introduction ........................................................................................................... 82
5.2 Literature Review .................................................................................................. 85 5.2.1 KPrIs in construction. .................................................................................... 85 5.2.2 BIM and the level of adoption. ...................................................................... 88
5.2.3 OSM and the level of adoption. ..................................................................... 89 5.2.4 The concept of interactions. ........................................................................... 91
5.3 Review Approach .................................................................................................. 92 5.4 Data Analysis and Findings .................................................................................. 95
5.4.1 The standalone OSM capabilities/functions for KPrIs. ................................. 99 5.4.2 The standalone BIM capabilities/functions for KPrIs .................................. 102 5.4.3 The interaction of BIM and OSM for KPrIs ................................................ 107
5.5 Integrated Framework ......................................................................................... 113 5.6 Discussion and Conclusion ................................................................................. 116
Chapter 6: Appraisal of Potential Interactions Between Building Information
Modelling and Off-Site Manufacturing for Project Performance .......................... 118
Abstract ........................................................................................................................ 118 6.1 Introduction ......................................................................................................... 120 6.2 Literature Review ................................................................................................ 122
6.2.1 Construction productivity. ........................................................................... 122 6.2.2 Project Performance ..................................................................................... 123
6.2.3 Background on OSM. .................................................................................. 124 6.2.4 Background on BIM. .................................................................................... 125 6.2.5 Interaction between OSM and BIM. ............................................................ 126
6.3 Research Model and Hypothesis Development .................................................. 127
x
6.3.1 BIM and project performance. ..................................................................... 127
6.3.2 OSM and project performance. .................................................................... 128
6.3.3 OSM–BIM interactions and project performance. ....................................... 129 6.4 Research Approach ............................................................................................. 130 6.5 Data Analysis and Findings ................................................................................ 136
6.5.1 Data collection. ............................................................................................ 136 6.5.2 Reliability of constructs. .............................................................................. 137
6.5.3 Hypothesis testing and interpretation. .......................................................... 139 6.6 Discussion and Contributions ............................................................................. 142 6.7 Conclusion........................................................................................................... 144
Chapter 7: Research Contributions .......................................................................... 147 7.1 Introduction ......................................................................................................... 147
7.2 The Satisfaction of Research Objectives and Research Contributions ............... 147
7.2.1 To identify productivity fundamentals and highlight the role of advanced
techniques for productivity improvement .................................................... 147
7.2.2 To investigate the current influential standalone capabilities of BIM and
OSM for a hybrid OSM–BIM conceptual framework ................................. 148 7.2.3 To identify the potential interactions of BIM and OSM for improving
productivity .................................................................................................. 148
7.2.4 To determine the influences of the standalone capabilities of OSM and
BIM, as well as their interactions in project performance ........................... 149
7.3 Overall Research Contributions .......................................................................... 150 7.4 Conclusion........................................................................................................... 151 7.5 Limitations, Recommendations and Future Research Directions ....................... 152
7.6 Summary ............................................................................................................. 154
References .................................................................................................................... 155
Appendix A .................................................................................................................. 202
Appendix B ........................................................................ Error! Bookmark not defined.
Appendix C .................................................................................................................. 210
Appendix D .................................................................................................................. 212
Appendix E .................................................................................................................. 213
Appendix F ................................................................................................................... 214
Appendix G .................................................................................................................. 215
Appendix H…….…………………………………...…………………………….……...….216
xi
List of Tables
Table 2.3 Advanced techniques and their effects on construction projects .................... 48
Table 2.4 Productivity fundamentals .............................................................................. 54
Table 5.1a Peer-reviewed publications in the proposed research areas ........................ 95
Table 5.1b Summary of the papers on BIM, OSM and performance .............................. 99
Table 5.2 Nominated KPrIs affected by OSM functions ................................................. 99
Table 5.3 Nominated KPrIs affected by BIM functions ................................................ 103
Table 5.4 A summary addressing the improvements achieved via OSM–BIM
interactions ................................................................................................... 108
Table 6.1 SEM measurements ....................................................................................... 131
Table 6.2 Reliability statistics ....................................................................................... 137
Table 6.3 Measurement scale and properties of constructs .......................................... 138
Table 6.4 Hypothesis test results ................................................................................... 139
Table A.1 Measurement of key constructs .................................................................... 202
xii
List of Figures
Figure 1.1. OSM–BIM in Deming cycle. .......................................................................... 7
Figure 1.2. Research procedures. .................................................................................... 23
Figure 2.2. Productivity fundamentals to reinforce advanced techniques. ..................... 55
Figure 4.1. The general feature of the hypothesis. .......................................................... 61
Figure 4.2. The variables of project performance. .......................................................... 63
Figure 4.3. General OSM capabilities. ............................................................................ 67
Figure 4.4. Main BIM capabilities/practices. .................................................................. 71
Figure 4.5. A conceptual framework to develop a hybrid OSM–BIM system for
project performance. ...................................................................................... 78
89
Figure 5.2. The potential practices of BIM in construction projects. ............................. 89
Figure 5.3. The selection process for the literature review. ............................................ 94
Figure 6.1. Hypothetical research model. ..................................................................... 127
Figure 6.2. Flowchart of research stages ....................................................................... 131
Figure 6.3. SEM model ................................................................................................. 141
Fig 7.1. Conceptual framework of smart construction for smart city ........................... 154
xiii
Glossary of Terms
BIM Building Information Modelling
CAD Computer Aided Drafting
KPrIs Key Productivity Indicators
SEM Structural Equation Modelling
OSM Off-Site Manufacturing
POBIs Potential OSM–BIM Interactions
TQM Total Quality Management
UK United Kingdom
US United States
WBS Work Breakdown Structure
3D 3 modelling/Dimensional
CA Constructability assessment
ME Measurement/estimation
CD Clash detection
SC Sequence clarification
SMB Safety management
PS Planning and scheduling
SC Site coordination
AP Automation and series production
SM Safety management
ISLM Interaction of Sequence and location management
IPS Interaction of Planning and scheduling
ISM Interaction of Safety management
IST Interaction of sustainability
IIM Interaction of Interface management
ICC Interaction of Contract condition
IIT Interaction of Information technology
xiv
IVE Interaction of Value engineering
ICE Interaction of Concurrent engineering
Qt Quality
Ct Cost
Tm Time
Sf Safety
1
Chapter 1: Introduction
1.1 Introduction
This chapter details the development of the thesis structure. As the beginning of
this chapter, it elaborates on the research background and the aim of the research. This
is followed by an exegesis of the thesis structure, which discusses the five underpinning
objectives of the research. Research methodologies used in this research are also
explained in this chapter.
1.2 Research Background and Aim of the research
Business competition and demands, cultural changes and constant environmental
changes have made the construction industry one of the most complicated industries
currently. Growth in the construction industry means that the selection of the
conventional design–build method does not sufficiently respond to high demands of
project performance anymore (Xia et al., 2013). Gross domestic product (GDP) is one
of the most significant indicators in determining the economic status of a country.
China, as one of the industry leaders, has been benefiting from considerable savings on
GDP from the modernisation of its construction industry. Considerations for increasing
productivity through manufacturing have contributed to GDP improvement in Malaysia
as well as Australia (Ibrahim et al., 2010; Khalfan & Maqsood, 2014). Even a small
productivity improvement in the construction industry can be remarkable and can
significantly contribute to national GDP improvements in Australia, as well (Khalfan &
Maqsood, 2014). Addressing inefficiencies and ineffectiveness in executing
construction projects have always been on top of the agenda. Many new techniques
based on different management approaches have been developed to reduce and
eliminate inefficiencies and ineffectiveness. The stakeholders in the Malaysian
construction industry have realised that there is a need to unify a project, throughout its
2
lifecycle, to avoid the issue of fragmentation in industrialised buildings (Mohammad,
Shukor, Mahbub, & Halil, 2014; Nawi, Lee, Azman, & Kamar, 2014). The core of the
issue has been labelled ‘communication-conflict interaction’ (Wu et al., 2017 p. 1466).
That is, the parties involved in a project need to be linked to each other to minimise the
chances of any potential conflict, and the huge amount of information generated needs
to be shared among the parties. Computer-based information systems are among the
new arrivals in the construction industry that have attracted attention in this regard.
Construction decision-makers, including clients and consultants, expect
construction contractors (as a sub-organisation partnering in a project) to adopt
measures such as appropriate management methods, professional workforces and
modern technologies to satisfy the productive supply chain (Beach et al., 2005).
As a new technique, BIM still raises doubts, questions, reluctance and
misunderstandings among construction professionals about its potential benefits and the
correct, consistent and influential level of BIM use to push projects forward through the
current challenges in the industry (Barlish & Sullivan, 2012). Estimator professionals
believe that BIM can optimise the estimation process dramatically, but there are some
barriers; for example, the full and accurate model for the quantity surveyors needs to be
accessible (McCuen, 2015; Smith, 2016).
1.2.1 The need for productivity improvement.
Construction improvement has attracted the attention of governments in such a
way that huge research funds are assigned to achieve it, as a priority. The UK
government has asked contractors to improve their productivity, as the main leverage
for success, via advanced managerial strategies and tools, consistent with the
competitive market. Offering projects with reasonable quality at the fastest pace of
progress, and with lower costs, is directly linked to companies’ survivability and
3
profitability in the competitive market. Productivity is an influential factor, which
determines whether a company will be selected to perform a project (Thomas &
Sudhakumar, 2012). As far as the response to the demand for productivity is concerned,
companies could either benefit or lose (Mahamid, 2013).
Low productivity is caused by ineffective strategies in running a project. This
issue results in loss of control of the construction process. The project, under these
circumstances, would face delay so that the interests linked to the project would be lost.
Productivity growth equals time and cost optimisation which benefit stockholders, and,
in many countries, low-productivity projects have been criticised in the construction
industry (Kagioglou et al., 2001).
Productivity growth is a managerial scheme. Therefore, an appropriate strategy
to embrace new techniques could accelerate that growth. Different themes, such as
cultural, educational, technical and organisational could remove the barriers to
improvement (Rojas & Aramvareekul, 2003).
Rethinking construction concepts has brought about new ideas to limit
inefficiencies in the industry. For instance, it is believed that new managerial styles,
such as ‘lean’ could create efficient resource availability (Thomas, Horman, Minchin, &
Chen, 2003) via site management skills, appropriate planning, effective administration
and implementation and continuous project control within the whole life cycle (Aziz &
Hafez, 2013). Without the correct recognition of productivity indicators, productivity
growth would not be possible. The potential of productivity growth could be achieved
through five areas: information technology, project delivery, automation and
prefabrication, workforce development, and materials suitability (Enshassi,
Kochendoerfer, & Abed, 2013).
4
It has been observed, through the literature review, that the factors affecting
construction productivity can be categorised under a wide range of indicators, such as
company’s characteristics, labour, material, management, regulation, machinery,
contract conditions, information technology, engineering, labour improvement and
external circumstances (Takim & Akintoye, 2002; Cox, Issa, & Ahrens, 2003; Bassioni,
Price, & Hassan, 2004; Chan, 2009; Chan, Scott, & Chan, 2004; Meng, 2012; Kapelko,
Horta, Camanho, & Lansink, 2015; Poirier, Staub-French, & Forgues, 2015). These
indicators can be categorised as the key productivity indicators (KPrIs).
The number of factors contributing to productivity growth differs between
different sectors. Arditi and Mochtar (2000) state that ‘the functions that were identified
as needing more improvement were new materials, value engineering, prefabrication,
labor availability, labor training, quality control’(p.150). OSM sectors constantly
achieved better productivity improvement among the improvable factors (Eastman &
Sacks, 2008).
1.2.2 Value-making approaches (VmAs).
Efforts via VmAs approaches focus on the elimination of inefficiencies and
ineffectiveness. These approaches recommend applying systematic innovative methods
to remove unnecessary costs, promoting quality and performance through teamwork and
unifying activities for value improvement (Smith & Colgate, 2007).
1.2.3 Total quality management and Deming cycle.
Management style, as one of the tools in managers’ hands, can help to achieve
reasonable productivity levels (Male et al., 2007). To successfully conduct a project,
proper management styles and techniques must be widely discussed, regarding planning
and time, cost and quality control (Munns & Bjeirmi, 1996). A managerial approach
clarifying constructive concepts and tasks can contribute significantly to achieving the
5
goals in a project. Therefore, a proper management style welcoming any action to
improve productivity can also contribute significantly to the perfect completion of
construction projects (Walker, 2015).
Quality management systems originated from the concept of total quality
management (TQM). The achievement of the objectives of these systems is subject to a
well-organised, functioning system and integrated stakeholders (Klufallah, Hasmori,
Said, & Idris, 2010). Continuous improvement is one of the principles in TQM, which is
achievable in the Deming cycle. As clients’ satisfaction is followed by continuous
improvement, it can be claimed that the Deming cycle is the core of the TQM concept.
The Deming cycle has been defined and explained in different sources, such as PM
book and ISO standards. It involves four procedures: planning, doing, checking and
acting. Generally, quality comes from this concept (Sokovic et al., 2010). Development
of value-making approaches (VmAs) in the construction industry has been on the
agenda at governmental forums. As pointed out, total quality management method
targeted to create value via the improvement of quality. Every consideration
contributing to the optimisation of the dimensions of project performance, which
include time, cost, quality, safety and stakeholders’ satisfaction, refers to values. The
application of advanced techniques, such as OSM and BIM, has been considered to
create value.
1.2.4 Statement of the problem and research gap
Among the new techniques, BIM, as an IT-based technique, has been introduced
to complement off-site manufacturing (OSM). There are positive point of views among
the professional to maximise the capabilities of these techniques by paring up BIM and
OSM, but there has not been a systematic direction of adopting them concurrently. In
recent years, advanced techniques, such as prefabrication, automation and IT-based
6
techniques, have drastically altered the construction industry, changing its focus from
traditional practice to modern enterprise (Nam et al., 2019). Building information
modelling (BIM) is recommended as an effective tool to meet project success criteria.
Its application leads to ‘improving actions towards technology transfer into
productivity’ (Zhang et al., 2015). Zhang et al. (2015) believed that BIM, as a new
technique, has potential to become the predominant technique used in the construction
industry for productivity improvement. Goodier and Gibbs (2007) claimed that OSM-
based projects observe a perfect project completion. They described OSM as a
technique to improve productivity in which off-site components and on-site structures
are combined in an optimum period. Although there have been issues on OSM-based
projects, Industry professionals and academics from countries such as Australia, the
UK, Malaysia, Hong Kong and Singapore have argued that the advantages of OSM
outweigh its disadvantages (Blismas, 2007). Therefore, further efforts are needed to
prove that OSM and BIM can be used to optimise construction projects in terms of time,
cost and quality performance.
Based on the literature available, attempts to combine OSM and BIM to improve
productivity are still in their infancy. It seems that there are still conflicting ideas among
decision-makers in this regard, either owing to overlooking details or negligence in their
evaluation (Hosseini et al., 2018).
1.2.5 The idea of BIM in OSM
New techniques and materials have changed the construction industry in recent
decades. Some highlighted new techniques include GIS, Big data, Virtual reality,
Augment reality, BIM, OSM, etc. have attracted the industry's stakeholders. As
different countries have their policies to adopt these new techniques, some reports
inform a lack of objectives fulfillment expected via some techniques. To solve this
7
problem, some researchers have recommended combining some of the techniques. They
provide the client and the stakeholders with some evidence on the capabilities of these
interactions. Among those techniques, BIM in OSM and BIM in Lean construction have
been identified to improve the construction industry. This research study focuses on
fostering the idea of BIM in OSM.
The current research aims to pair up OSM and BIM functions and practices for a
systematic adoption to maximise benefits. Seemingly, BIM specifications are very
capable of being integrated into the Deming cycle concept in OSM-based projects.
Figure 1.1 indicates that there should be some inbounding points, so that the
capabilities, function and practices of the two techniques are injectable into the cycle, to
optimise the product. This reflects a unique systematic adoption of BIM in OSM-based
projects.
Figure 1.1. OSM–BIM in Deming cycle.
Based on the explanations above, the following question needs to be addressed:
‘How can BIM be properly applied in the OSM-based projects to fulfil the objectives of
both techniques in the productivity improvements followed by project performance?’
Therefore, this research aims to:
Determine the influences of OSM–BIM interactions on project productivity that
result in project performance.
8
1.3 Exegesis of Thesis Structure
An extensive, in-depth review of the role of OSM and BIM as advanced
techniques in construction productivity, followed by a data analysis, allows for a better
understanding of this research.
First, this chapter explains how the subset objectives address the aim of the
research. A micro-to-macro method was used to assemble the relevant literature. Each
dimension of this two-dimensional view interacts with the other, for a more efficient
analysis of the application of the advanced techniques (Wagner & Derryberry, 1998).
The micro-dimension examines the discovery of individuals and their interactions that
may contribute to a framework. The macro dimension examines the impact of the
discovered individual contributor and any potential interactions in a functioning system.
The outcomes achieved through the micro-level method are the prerequisite of any
actions at the macro-level method (Billari, 2015). In this research, the micro dimension
examines the range of productivity fundamentals and identifies the KPrIs. This results
in a supplementary foundation, on which advanced techniques, specifically OSM and
BIM, should be applied. The macro dimension determines the practicality of using
OSM and BIM throughout the project stages that can improve the KPrIs.
Therefore, the objectives have been developed as follows:
1.3.1 Pathways for the improvement of construction productivity: A
perspective on the adoption of advanced techniques.
The first objective of this thesis is formulated as follows:
Objective 1: to identify productivity fundamentals and highlight the role of
advanced techniques for productivity improvement.
The construction industry plays a significant role in the economy of any
countries. Fragmentation issues, improper choice of techniques and inappropriate
9
management result in inefficiencies such as cost and time overrun, which fall under the
theme of poor productivity (Bresnen, & Marshall, 2000; & Ganesan, 1984). This issue
has always challenged both the stockholders’ presence in the competitive market and
clients’ profitability. Fundamental changes have been suggested to improve productivity
(Force, 1998). Researchers and practitioners have been invited to develop new strategies
to overcome these challenges. The theorisation of the new strategies and techniques,
followed by their successful establishment, requires a strong leadership, recognition of
customers’ needs, influential collaboration and a proper project process. The innovation
of advanced techniques and integrating systems are subject to the recognition of weak
points and the perpetration of a range of fundamental supports in the current
circumstances (Changali et al., 2015; Winch, 1998). A quick decision-making process is
inseparable leverage for a successful, functioning system (Changali et al., 2015).
Undoubtedly, the lack of contract clarification can appear as a disturbing agent, even
though a properly functioning system is in place and an appropriate advanced technique
is implemented. The advanced techniques are to deal with project performance via key
productivity indicators. Cost benefit analysis and return on investment (ROI) have been
used to evaluate project performance from the implementation of the new techniques
and technologies. However, those techniques can not cover all areas of KPrIs and need
to be reinforced by a range of fundamentals contributing to the final productivity. This
argument provides practitioners with a holistic understanding of the root of poor project
productivity and the pathways through which the new, advanced techniques can affect
different aspects of performance. The range of productivity fundamentals can act as
catalysts or reinforcers that contribute to the improvement of the functioning system in
the implementation of the advanced techniques.
10
Chapter 3 of this thesis has been published as an article, which fulfilled this aim.
A wide, scoping review of 128 academic publications contributing to productivity
fundamentals and advanced techniques was made. This study discovered a range of
productivity fundamentals (Table 3.1), which were applicable where the capabilities of
the new advanced techniques could not cover all areas of KPrIs and the integration of
these fundamentals is required. Figure 3.2 conceptualised a generic pathway that linked
the productivity fundamentals and the advanced techniques to the final project
performance.
1.3.2 The current influential standalone capabilities of BIM and OSM for a
hybrid OSM–BIM conceptual framework.
The second objective has been developed according to the following
explanations.
Objective 2: To review the current influential standalone capabilities of BIM and
OSM for a hybrid OSM–BIM conceptual framework.
The development of influential, advanced techniques, underpinned by
technology evolution, have been noted as a solution to construction productivity. Every
technique, with its own specific objectives and capabilities, aims to upgrade the
construction industry. However, the fulfilment of some objectives has faced challenges
in practice and the outcome has been far behind what was theorised. These techniques
are not able to cover all areas of productivity improvement. Some researchers have
found it useful to combine IT-based advanced techniques (Zhu & Augenbroe, 2006)
with the other newly advanced techniques. They believe that the concurrent application
of the techniques can cover one another and can enhance the projects’ output
(Segerstedt & Olofsson, 2010). They argued that the weak points of one technique could
be overlapped by the strength of the other technique. Therefore, the level of productivity
11
improvement could be better enhanced. Some construction practitioners have criticised
OSM for the inefficiencies reported from OSM-based projects. They found that the
fragmentation among the parties and lack of clarification regarding the specifications of
manufactured components disturb the assembly process and eventually distract from the
productivity trend. BIM, as an IT-based technique, has been noted as a potential support
for OSM to overcome these challenges, but this evolution takes time and effort—from
idea formulation to the establishment of an OSM–BIM hybrid technique. The first step
to this end is to conceptualise how to pair up these two techniques.
A publication, recorded in Chapter 4, shows how to achieve the second
objective. Figure 4.5 is the hybrid conceptual framework for the overall project
performance, drawn after the deep review of 47 academic publications, to gain the
required understanding to formulate the idea of BIM in OSM.
1.3.3 The identification of potential interactions between BIM and OSM for
productivity improvement.
The third objective is formulated as follows:
Objective 3: to identify potential interactions of BIM and OSM for productivity
improvement.
‘Productivity rate’ refers to the coefficient obtained from dividing the input
(what is required to progress the construction) by the output (the value of the
construction progress). Productivity is aligned with project performance. This means
that the productivity indicators deal with performance criteria. Therefore, identifying the
KPrIs and improving them can guarantee the project performance. Low construction
productivity has been flagged for decades and authorities have asked for solutions to
overcome this crisis. The development and application of new, advanced techniques has
been advised by researchers to upgrade construction methods (Blayse & Manley, 2004).
12
Some newly emerged techniques could not satisfy the productivity expectations—
contrary to what had been claimed in theory. BIM and OSM are the new revolutionary
techniques, but there are still arguments that they have not fulfilled their objectives for
productivity improvement. A limited number of researchers believe that OSM-based
projects can be supported by BIM (Goulding, Pour Rahimian, Arif, & Sharp, 2012).
However, a systematic adoption of OSM–BIM-based projects has not been addressed
yet. In this regard, a conceptual framework of KPrIs is needed. Following that, the
standalone capabilities of the two techniques need to be scanned, to inform how they
should be paired up for a range of practical interactions to improve KPrIs.
Chapter 5 is a publication discussing the achievement of the third objective. It
involved critically reviewing 100 academic publications to support the objective. Figure
5.1 shows a demographic framework of KPrIs. The methodology pathways are shown
in Figure 5.3. Table 5.2 and 5.3 show the nominated KPrIs that can be improved by the
two techniques individually, while Table 5.4 shows the indicators affected by OSM–
BIM interactions. Overall, 12 potential interactions were identified between OSM and
BIM to improve KPrIs. Figure 5.4 conceptualises how the capabilities of OSM and BIM
can affect project performance at the pre-construction and construction stages.
1.3.4 The influences of interactions between BIM and OSM on project
performance via productivity improvement.
The fourth objective has been developed as follows.
Objective 4: to determine the influences of the standalone capabilities of OSM
and BIM, as well as their interactions, on project performance.
Irresponsive productivity levels in the construction industry have led authorities
to encourage fundamental changes in construction methods. Numerus studies have been
carried out to upgrade the industry, but the industry is still struggling to satisfy the
13
clients and the stockholders’ expectations of productivity (Barbosa et al., 2017).
Although advanced techniques have considerably affected the industry, productivity is
still lagging below a satisfactory level (Sabet & Chong, 2018). The systematic adoption
of BIM provides other techniques with overlapping capabilities that might maximise
their functionality. For example, BIM, as a technique, and providing a collaborative
environment, can pair up with lean (Sacks, Koskela, Dave, & Owen, 2010). Nawari
(2012) and Wynn et al. (2013) believe that BIM, with its IT-based nature, enhances
efficiency in OSM. Potential interactions between BIM and OSM have been found to be
capable of improving KPrIs to meet project performance criteria. These interactions are
capable of being applied in the planning and managerial stages (Sabet & Chong, 2019).
Sabet and Chong (2019) have hypothesised relationships among three units, namely,
BIM capabilities, OSM capabilities, OSM–BIM interactions and project performance,
to evaluate the practicality of the interactions.
The capabilities and the interactions were put in the judgement of construction
practitioners to determine their relationships with the project performance.
The pathway of how to achieve the fourth objective is discussed in Chapter 6.
Based on this discussion, a publication is under review. The hypothetical model was
tested via SEM, using AMOS software. Figure 5.3 reveals the degree of influence of
each capability and their interactions. This figure also shows the direct and indirect
influences of OSM, BIM and a hybrid OSM–BIM techniques on project performance
(via KPrIs), once they are applied individually and concurrently.
1.4 Summary
This chapter has highlighted a gap in productivity fundamentals, which are
required to reinforce the implementation of new advanced techniques for productivity
improvement. It was argued that the capabilities of the advanced techniques could not
14
cover all the areas of productivity indicators. Then, the research focused on a systematic
adoption of BIM in OSM-based projects, among the other advanced techniques. The
systematic adoption was referred to an effective and efficient application of BIM, to
eliminate inefficiencies in time, cost, quality, safety and stockholders’ satisfaction in
OSM-based projects. In addition, the measures to pair up the capabilities of these two
techniques were referred to as the development of OSM–BIM interactions. These
interactions affect KPrIs, which supports project performance. The research
methodology was also discussed in this chapter.
15
Chapter 2: Research Methodology
A description of research methodology details the type of data that the study
required, the sampling method, the manner in which potential respondents were
approached and the data collection and analysis techniques (Easterday, Rees Lewis, &
Gerber, 2018; Choy, 2014). In this research, a quantitative research methodology was
established to achieve the aim of the study through an inductive approach. This chapter
clarifies the research strategy and applicable terms.
2.1 Research
Research involves conducting observation, analysis, survey, experiments, study,
reasoning, comparison and other activities to accurately achieve results in a standardised
and organised fashion, based on verifiable facts, which may solve issues in societies or
scientific fields (Towne & Shavelson, 2002). Shuttleworth (2008) specified that
research is a systematic procedure to find new information. This study provides a
framework for systematically adopting a concurrent application of OSM and BIM
techniques. This type of research can play a great role in expanding and improving
certain fields such as the development of theories and diffusion of innovation. Bunge
(2012) stated that, based on research findings, researchers can anticipate future events,
establish and promote ideas, and form conjectures about the relationships between
variables. Therefore, research can have the function of developing theories formed or
suggested in previous studies.
2.2 Inductive Approach
The term inductive approach, or inductive reasoning, refers to the approach of
developing a theory based on pieces of evidence. Observations are made at the
beginning of the research and the theory is developed in almost the final stage
(Sabherwal & King, 1991). This type of research aims to discover a pattern by
16
extending existing evidence by developing and evaluating hypotheses during the study.
Research with an inductive approach is not initiated based on any theory, and hence, the
researcher can change course and test hypotheses with a view to moving towards
meaningful answers to the research questions (Thomas, 2006). The basis of this
approach is learning from existing knowledge and experience, that is, drawing
conclusions or building theories (Jebreen, 2012).
The aim of this research was informed by existing evidence pertaining to the
combined use of BIM and OSM as advanced techniques. Subsequent data collection and
analysis revealed more evidence, which developed the domain of interactions between
OSM and BIM and provided a basis for examining their potential for use in productivity
improvement.
2.3 Research Methodology
2.3.1 Quantitative methodology.
A quantitative research method aims to answer questions about potential
relationships and the degrees of effects among variables. The inputs in quantitative
research comprise numerical and standardised data (Martin & Bridgmon, 2012). Martin
and Bridgmon (2012) explained that interpreting results obtained through this method is
uncomplicated because they are numerical values, which are obtained by assessing
participants’ performance, behaviours and opinions. The data collected in this type of
research can be extended to larger populations. Moreover, the data can be efficiently
explained in the form of quantitative graphs and charts.
Munn, Porritt, Lockwood, Aromataris and Pearson (2014) claimed that
quantitative research is based on confidence and certainty because it has the features of
empirical studies, in which practical symbols are used for every phenomenon and truth
is signified. This means that researchers can explore every incident and avoid being
17
affected by, or affecting, that incident. Analysing and interpreting the findings in this
type of research is quantifiable because it directly relies on its original plans.
2.4 The research methodology of this study
This hybrid thesis contains four academic publications (three published and one
under review) to meet the research objectives in chapters 3, 4, 5 and 6. The research
methodology for each objective is comprehensively discussed in the relevant chapters.
The following sub-sections provide a brief overview.
2.4.1 The research methodology to meet the first and the second objectives.
The implementation of advanced techniques has previously been identified as a
potential solution to a lack of project productivity. However, the expected level of the
productivity that lies in project performance has remained a challenge. The first
objective was to identify productivity fundamentals and highlight the role of advanced
techniques for productivity improvement. As the objective implies, productivity
fundamentals and advanced techniques were the two units examined. To this end, a
micro-to-macro level search was required to satisfy the objective. A comprehensive
scoping review was applied (a) to identify the root of poor productivity, upon which a
range of productive fundamentals was to be developed; (b) to identify the stages at
which these fundamentals must be applied; and (c) to highlight the pathways through
which the common advanced techniques improved project performance. The scoping
review was also tasked with identifying potential gaps that caused performance level to
be lower than expected even after applying advanced techniques’. The second objective
of this research was to investigate the current, influential standalone capabilities of BIM
and OSM for a hybrid OSM–BIM conceptual framework. An extensive and in-depth
scoping review was required to clarify each technique’s capabilities and construct an
OSM–BIM hybrid foundation. Literature surrounding BIM and OSM was collected.
18
Papers that clarified project performance were also selected. The papers were filtered
based on their abstracts to ascertain whether the papers had information that would
clarify the capabilities of the two techniques. An analytical and critical perspective was
applied to scan the papers. Subsequently, the idea of combining OSM and BIM for
systematic adoption was fostered and formulated.
A literature review surrounding resources, management, engineering and
innovation was necessary to substantiate the appropriateness of the units of construct in
this research. Literature in these areas was collected, filtered and scanned, then
assembled into a collection of relevant materials. Figure 3.1 shows the methodology to
achieve the first objective.
2.4.2 The research methodology to meet the third objective.
Existing literature that suggests applying BIM in OSM does not describe a systematic
adoption framework for pairing the capabilities of the two techniques. However, every
constructive interaction is subject to systematic adoption. The capabilities could
potentially overlap regarding project productivity. Identifying the KPrIs was necessary
to discover the pathway through which potential interactions could improve them.
Therefore, the third objective was to identify potential interactions between BIM and
OSM for productivity improvement. The literature review comprised a scoping review
and systematic review. The scoping review was used to gain a holistic understanding of
the elements of the study, while the systematic review summarised all relevant papers
regarding BIM in OSM. The process started with the scoping review. Six categories were
identified as indicators in construction productivity (either individually or
synergistically), namely resources, management, engineering, procurement and contracts,
information technology and sustainability. The second stage involved searching the
channels of evidence, including the collection and filtration by type of literature. Relevant
19
papers were identified by keyword searches in Google Scholar and library databases, and
their relevance was assessed by examining their abstracts. Figure 5.3 shows the selection
process for the literature review. The question of how the potential OSM–BIM
interactions could improve construction productivity was pursued.
2.4.3 The research methodology to meet the fourth objective.
Determining factors for selecting a suitable research methodology include limitations
such as budget and time shortages, research potential, and the willingness of (human)
subjects (Brannen, 2005). The research methodology must ensure that data will be
unvarying and consistent (reliability), and that the unessential and unrelated variables
are excluded so that the final instrument can measure the targeted variables accurately
(validity) (Golafshani, 2003). As pointed out earlier in this section, this research aimed
to measure the individual capabilities of BIM and OSM techniques, the practicality of
interactions between them. Therefore, in the first round of the pilot study, the authors
approached several leaders in the industry and academia to determine how to effectively
convince the respondents to participate in the study. A quantitative method was advised,
based on the potential desires of respondents within the study scope.
Martin and Bridgmon (2012) explained that interpreting results obtained through this
method is uncomplicated. The results are numerical values, which are obtained by
assessing participants’ performance, behaviours and opinions. Munn et al. (2014)
claimed that quantitative research is based on confidence and certainty because it has
the features of empirical studies, in which practical symbols are used for every
phenomenon and truth is signified.
After the first round of pilot study, the authors applied two more rounds of pilot studies.
In the second round, for construct validity, the authors double-checked the measurement
constructs with the leaders from the first round. In the third round, observable variables
20
were discussed with several experts and seniors who had a holistic understanding of
both approaches. In other words, for content validity, the authors developed the
statements indicating the potential applicability of the capabilities and interactions. At
this stage, the authors ensured that the statements were in a digestible format and able to
accurately measure the targets. After data collection stage, the hypothetical model was
evaluated using SEM, through Amos software. Cronbach’s alpha was used to evaluate
the data reliability. In addition, regression tests were applied to identify the existence of
any relationships and reveal the variables’ degrees of influence in the hypothetical
model.
Figure 6.2 depicts the stages of this part of research. The first stage involved a
literature review of BIM, OSM and BIM in OSM, followed by the identification of gaps
in research. In Chapter six, six hypotheses were developed to evaluate the relationships
between latent and observable variables. Table 6.1 displays the constructs and the
observable variables by which the latent variables could be measured. Observable
variables were discussed with several experts and seniors in the industry and academia
who had a holistic understanding of the two approaches. Their wealth of experience in
academia and the industry facilitated the identification of observable variables, which
were then used to develop a questionnaire as the data collection tool for this study.
Australia was selected as the location of this research study. Construction
practitioners with relevant expertise were provided with a Qualtrics survey link. Paper
questionnaires were also distributed. Engineers Australia significantly supported this
research. The research was officially introduced to their members, who were
encouraged to participate in the survey. Subsequently, the research team approached
those practitioners through LinkedIn and advised them about the research. LinkedIn was
observed to be the best platform to learn about the background of potential participants.
21
Practitioners’ profiles allowed the research team to target those who were
knowledgeable about, or experienced in, OSM and BIM. Additionally, the research
team met with several seniors in academia and representatives of construction
companies, in person and virtually. Prior to conducting the survey, the
comprehensibility and validity of the observable variables was tested in the pilot study
with ten randomly selected construction practitioners. The hypothetical test results
determined whether the hypothetical model was successful or needed revision. The
result showed that two out of six hypotheses were not supported.
2.5 Summary
A wide literature review, including the scoping and systematic reviews, was
conducted to scan the productivity fundamentals and indicators and the capabilities of
the advanced techniques, with a focus on OSM and BIM, to identify any potential
interactions between them followed by an empirical study to evaluate the hypothetical
model of relationships between the two selected techniques.
A quantitative research methodology was used to achieve the aim of the
research. To evaluate the validity of the hypothetical model, an online survey on the
application of the two techniques among construction practitioners was performed. The
collection of data involved 687 construction practitioners in different regions of
Australia. They were involved in the planning, design, construction, engineering,
contract and procurement. They were approached via LinkedIn, e-mail and face-to-face
meeting. The questionnaire included questions related to their understanding of the two
techniques, obtained via academic studies and professional experience.
To investigate the relationship between the research units, a Likert scale ranging from
one to five (such as, from ‘strongly agree’ to ‘strongly disagree’) was used. A two-
round pilot survey was conducted to revise the questions. The data from the valid
22
questionnaires were analysed via structural equation modelling (SEM) using AMOS
software. This method was selected because of the capacity of SEM-based method to
deal with complex models (Rigdon et al., 2017). The research procedures have been
consolidated and explained in a flowchart approach to make clear the overall research
methodology, are shown in Figure 2.2.
23
Figure 2.2. Research procedures.
Studies to
identify the gaps
&problems
To develop.the
research
questions
To identify
objectives
Candidacy
submission&
approval
Survey design
In-depth
literature
review
(scoping&
systematic)
Pilot study
Validat
Co
rrec
tion
Questionnaire
distribution
Sampling/finding
Suitable
respondents
Data collection
Hypothetical
model
confirmation/
Revision
Data analysis
Aca
dem
ic p
ub
lica
tion
1
Aca
dem
ic p
ub
lica
tion
3
Aca
dem
ic p
ub
lica
tion
4
Aca
dem
ic p
ub
lica
tion
2
24
Chapter 3: Pathways for the Improvement of Construction
Productivity: A Perspective on the Adoption of Advanced
Techniques
Pejman Ghasemi Poor Sabet1; Heap-Yih Chong2
1School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia,
2School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia.
E-mails: [email protected]; [email protected]
Abstract
Reinventing construction is the key to improving productivity. This reinvention refers to
not only inventing advanced materials and equipment, but also to developing new
operating systems for construction projects. Inadequate application of advanced
techniques impedes the operating system. Further, the capabilities of advanced
techniques may not cover all areas required to meet the expected productivity level. The
implications of these advanced techniques need to be reinforced by a range of
productive fundamentals that remain unclarified. Further, the pathways through which
these fundamentals can be aligned with the implementation of advanced techniques
remain under-researched. Hence, the objectives of this research are: (1) to clarify how
the selected and common advanced techniques applied in this paper influence
construction productivity; (2) to determine the range of productivity fundamentals
required to reinforce the implementation of the advanced techniques necessary to fulfil
25
productivity expectations; and (3) to conceptualise the integration of these productivity
fundamentals with the application of advanced techniques. A scoping review of 128
articles was used to identify which fundamentals can contribute to achieving
performance targets once practising these new advanced techniques. The findings reveal
a comprehensive range of productivity fundamentals that are able to reinforce new
advanced techniques through different pathways of their applications.
3.1 Introduction
The construction industry is a major contributor to the gross domestic product
(GDP) of a country’s economy (He& Shi, 2019). The issue of the decline of
productivity in the construction industry (Stevens, 2014) has been put in the spotlight
due to failures to meet ever-changing performance expectations for half a century
(Sveikauskas et al., 2016; Green, 2016). Therefore, there is a need to bring productivity
out of this deadlocked state since the construction industry, directly and indirectly,
impacts the economy (Green, 2016) of both developing and developed countries. As the
main aspects of performance, inefficiencies in time, cost and quality in the Iron Triangle
not only result in client dissatisfaction, but also negatively impact the economy in a
broader sense. In the UK, a pioneer in the construction industry, this issue has caused
the authorities to consider construction re-engineering. The construction sector needs an
upgraded operating system to allow it to meet the expectation of productivity growth in
compliance with the pillars of the Iron Triangle as the primary performance constraints.
These constraints were later extended to five criteria, including time, cost, quality, scope
and risk (Bronte-Stewart, 2015). Sabet and Chong (2018) defined these criteria as time,
cost, quality, stockholder satisfaction and safety: the main aspects of construction
performance. The question of how to manage these constraints challenges companies
and authorities in the construction industry. New business models and upgraded
26
construction management have been required to eliminate the challenges associated
with meeting expected construction performance (McGeorge et al., 2012). An effective
project operating system that is supported by technological innovation is at the heart of
a better workflow (Changali, 2015). Management considerations and the
implementation of advanced techniques have not yet satisfied the requirements for
performance achievement. Those measures need to be reinforced by a range of
productivity fundamentals that can help to fulfil productivity objectives at different
stages of a project. The question arises as to which fundamentals can supplement the
capabilities of these advanced techniques.
Hence, this paper addresses a range of productivity fundamentals and clarifies
how they play a vital role in meeting performance goals once the required advanced
techniques have been implemented. The potential benefits may be useful to: (a)
developers of new techniques, who may use this study to establish upgraded technical
concepts for the updated productivity criteria linked to project performance; and (b)
practitioners who should consider these productivity fundamentals for the effective
implementation of advanced techniques.
3.2 Literature Review
3.2.1 Productivity requirements and issues.
The construction sector is a pillar of the GDP of a country. The income derived
from the construction industry is a significant proportion of GDP, as are the indirect
incomes that arise from marketing and operational services (Richardson, 2014). The
inefficiencies arising from the construction sector not only result in client
dissatisfaction, but also impact the economy due to low productivity. Lack of an
integrated management followed by fragmentation among the stockholders and have
27
been flagged as factors that reduce construction productivity in conventional
construction (Bresnen & Marshall, 2000; Ganesan, 2000).
Low construction productivity has always challenged stakeholders and clients.
Force (1984) stated that ‘clients need better value from their project, and companies
need reasonable profits to assure their long-term future’ (p.10). Development of new
strategies is an important task for researchers aiming to improve the industry.
Implementation of new techniques and technologies in process development has been
important in overcoming the challenge of low productivity. In this regard, fostering
commitment between the parties involved in a project appears to be one of the important
requirements of the process. Force (1984) stated that embracing change has been
identified as the key factor in successfully improving productivity in industry, but that
the construction industry has been very resistant to change. According to Force (1984),
a series of fundamentals of the project process, such as committed leadership, a focus on
the customer’s requirements, process and team integration, a quality-driven agenda and
commitment to the different stakeholders, are the radical changes required in the
construction industry. These necessary changes are impossible without properly
implementing new techniques and technology to increase innovation. Winch (1998, p.
268) stated that ‘the roles of the innovation infrastructure, innovation superstructure and
systems integrator are’ the fundamentals of the successful establishment of innovation
in the construction industry. Also, effective management of multi-cultural human
resources at different levels at job sites is another consideration fundamental to project
productivity and success (Enshassi, & Burgess, 1991; Fellows& Liu 2012). Moreover,
skilled benchmarking can play an important role in improving a construction project.
According to the report (1998) made by Task Force, practising these fundamentals
together are the only way to successfully implement new techniques and technologies.
28
Changali et al. (2015) argue that fast-growing investment, requests for larger shares in
megaprojects and poor completion of megaprojects determine the need for new
techniques and approaches that are consistent with the productivity expectations for
future projects. They believe that a range of measurements made at three stages of a
project; namely, concept and design; contract and procurement; and lastly execution,
can remove potential weaknesses reducing productivity. Also, Changali et al. (2015)
stated that slow decision-making and processes within an organisation can result from
inaccurate and poor reporting from team members and stockholders. In fact, this
shortcoming impedes communication between stakeholders and prevents prompt action
within a project.
Lack of clear contracts are another reason for productivity loss. In this case, the
negotiations required to manage any conflicts as they arise are complicated and may be
followed by a lengthy dispute resolution process. As different roles and activities are
defined at different layers within a project, suitable measures are required to network
these roles and control activities to avoid any interference in planning and scheduling
(resolution of the issue of fragmentation) (Fellows &Liu, 2012). Short-term planning
and taking alternatives to reinforce planning and scheduling are important
considerations to keep project progress on track. Further, a consistent management style
is central to ensuring that staff contribute their highest capacities and competencies to a
project (Enshassi &Burgess, 1991). Inappropriate risk allocation has also been reported
as a cause of inefficiencies; not involving stakeholders other than the contractor puts all
the responsibility for the project on the contractor.
Previous studies have largely focused on determining the productivity indicators
in construction projects from the perspective of value-creating approaches. Cost benefit
analysis and return on investment (ROI) have been used evaluate the performance
29
resulting from the implementation of new techniques and technologies. However, no
prior research has considered a generic pathway or the interactions between productivity
indicators and aspects of construction performance after the implementation of
advanced techniques in projects. This paper discusses the pathways through which the
new advanced techniques can impact different aspects of performance, and suggests a
range of productivity fundamentals that can act as catalysts or reinforcers that contribute
to the improvement of the operating system via the implementation of advanced
techniques. This paper claims overall project performance to be the output of a function
in which potential productivity fundamentals are aligned with the implementation of
advanced techniques.
As the literature implies, the factors affecting construction productivity can be
identified as delayed schedules, changed orders, materials mismanagement, unstable
weather conditions and human performance-related factors. Park (2006) claimed that
management considerations and environmental conditions play the determinant roles in
estimating productivity in construction. Bassioni et al. (2004) believed that identifying
the indicators affecting productivity that interact with new techniques can result in
successful productivity improvement. Table 3.1 categorises the factors threatening
productivity that have been identified in the literature. It may help developers of new
techniques to consider the actions required to eliminate weaknesses in the establishment
of future technologies and approaches.
30
Table 3.1
Potential roots of poor productivity
Potential roots of poor productivity Sources that contribute to confirm these
roots
Poor organisation El-Razek et al., 2008; Azhar et al., 2008
Inappropriate relationship management and
communication among stockholders
Durdyev& Ismail, 2016; Naoum, 2016;
Emmitt& Gorse, 2006; Meng, 2012
Ineffective management style Lavender, 2014; Kazaz& Ulubeyli, 2007
Lack of technical specifications and contract clarification Jarkas& Radosavljevic, 2012; Jaffar et
al., 2012
Lack of skilled crew members and inefficient connection
with the crew
Shohet& Laufer, 1991; Islam& Khadem,
2013; Jarkas& Bitar, 2011
Untracked planning/scheduling
(poor project control)
Aziz& Hafez, 2013
Lack of risk management allocation Mills, 2001; Wang et al., 2004
Competencies mismanagement Singh, 2010; Islam& Khadem, 2013
Lack of upgraded equipment, methods and materials Alwi, 2003; Ghoddousi et al., 2012;
Thomas et al., 2003
Lack of satisfactory working conditions Abrey& Smallwood, 2014; Hanna &
Heale, 1994
Improved construction performance is the result of productivity improvement
(Sabet & Chong, 2018). Force (1998) observed the potential for productivity
improvement by reducing capital costs, project duration, the number of accidents and
employee turnover and staff productivity. Hoehne and Russell (2018) reported that poor
construction productivity may be due to fragmentation of stakeholders, contract
mismanagement and an opaque marketplace. Therefore, a range of measurements of
these strengths and weaknesses can contribute to assessing the overall project
performance.
3.2.2 The debate on ROI.
This debate has been raised due to risk of the loss of value of investments. A
reasonable ratio of benefit to cost is expected from the ROI perspective. Time, cost,
quality, safety and stakeholder satisfaction are the pillars of ROI. Developing the range
31
of objectives is the first crucial step in ROI methodology, which sets out five crucial
levels of objectives at the concept and development stages to sell interactive
technologies. The objective levels include reaction objectives, learning objectives,
application objectives, impact objectives and a final ROI objective (Wagner &
Derryberry, 1998). These productivity requirements are the preliminaries for the ROI
perspective, and are crucial in developing new techniques and business models.
Different models may incorporate various costly stages. As an example, the cost of
quality model consists of several layers of quality achievement. This model determines
the costs of quality achievement within four areas: prevention costs, appraisal costs,
internal failure costs and external failure costs (Lindsay & Evans, 2010; Jafari& Love,
2013).
3.2.3 Emerging advanced techniques for construction projects.
As stated earlier, rethinking construction is necessary to reduce dissatisfaction
with overall construction performance. Force (1998, p. 4) identified four factors that are
important for resolving the issue of client dissatisfaction, including, ‘committed
leadership, a focus on the customer, integrated processes and teams, a quality-driven
agenda and commitment to people’. End-user dissatisfaction can originate from a lack
of stakeholder satisfaction with the project. Lack of stakeholder satisfaction results in
inefficiencies and vice versa, impeding project productivity. How to respond to the
interests of stakeholders and manage their reactions within an organisation is crucial
when managing stakeholders (Jepsen & Eskerod, 2009). Further, stakeholder
commitment regarding competent decisions made during the project improve company
performance (Song& Zhang, 2017). Therefore, the need to improve productivity has
paved the way for advanced and emerging techniques and technologies, each with their
own characteristics. In recent years, advanced techniques, such as prefabrication,
32
automation and IT-based techniques, have drastically altered the construction industry,
changing its focus from traditional practice to modern enterprise (Nam et al., 2019).
(Agazzi, 1998, p.2) referred to a technique as ‘a display of practical abilities that
allow one to perform easily and efficiently a given activity’. Isman (2012) defined a
technique as having the practical knowledge to contribute to a procedure or a system
and referred to technology as organising and practically applying knowledge to produce
a concrete result. As examples, modern construction is considered a technology Isman
(2012), while the lean production and prefabrication contributing to potential modern
construction are considered techniques. Therefore, the application of a new technique
may be followed by creation of a new technology. The interdependent implementation
of these advanced techniques, as well as their concurrent applications under a well-
defined, systematic adoption, form potentially value-making leverage for the
performance of construction projects (Nguyen & Akhavian, 2019).
Based on ‘productivity improvement strategies’ (Gunasekaran, & Cecille, 1998)
three steps can determine whether improvements are achieved by implementing new
techniques and technologies: first, setting clear objectives; secondly, putting in place the
pathways needed to achieve the objectives; and thirdly, sharing and comparing data to
assess performance with other practitioners in the industry.
The ROI perspective has been useful in creating a range of new approaches and
techniques, each with their own specific characteristics and particular potential to create
improvements. The following sections discuss these functions.
3.2.3.1 Big data.
These newly advanced techniques generate high volumes of useful data that can
contribute to improving productivity (Ismail et al., 2018). Therefore, they can be
categorised as big data-inspired techniques, which, by definition, deal with the large
33
amounts of information required for decision-making. The term ‘big data’ refers to an
industrial revolution brought about by the use of vast amounts of data—characterised by
volume, variety and velocity (the 3Vs)—for business improvement, cost optimisation
and prediction of revenue (Ismail et al., 2018). The three basic functions of big data are
recognition of customer priorities, prediction of market trends and business process
optimisation. This third function has been found to be applicable to the construction
industry and to improve cost-effectiveness. Cost reduction is the final outcome of the
comprehensive information on cost-effectiveness provided by big data-directed
techniques and tools. However, this requires a systematic workflow to extract the
information applicable to the decision-making process (Bilal et al., 2016). Innovation of
new services and products is a priority for reducing costs. An understanding of
customer expectations, consumer concerns and market prediction is an essential
preliminary of process optimisation—another great outcome of big data, which
contributes to the decision-making processes that influence the development of
innovation. Process optimisation can be found applicable to the construction industry,
which relies on cost-effective solutions. Bilal et al. (2016) believed that the 3Vs of big
data can influence productivity streamlining. However, this benefit requires a masterful,
systematic workflow to extract constructive materials applicable into the decision-
making process (Bilal et al., 2016). Shrestha (2013) declared that a range of diverse data
are generated within the phases of construction projects; these data are required to be
processed, streamlined and exchanged among stockholders during decision-making.
This diversity of data can reflect the 3Vs of big data that configure the pathway towards
improvements in efficiency during a building project’s lifecycle (Motawa, 2017).
Advanced techniques generate not only a high volume of data, but also effective
information that contributes to the improvement of productivity (Ismail et al., 2018).
34
Therefore, it is claimable that the techniques are aligned with the objectives of big data
concept and can be categorised as big data inspired techniques.
The techniques outlined in this section are categorised as big data-based
techniques, as their objectives are to provide the project’s operating system with
sophisticated information.
3.2.3.2 BIM.
A revolutionary emergence, BIM offers numerous precise and practical data to
the construction industry, from an improved computer-aided drawing (CAD) model, to
the involvement of project stockholders in a multidisciplinary working environment
(Eadie et al., 2013). BIM presents considerable potential for coordination, collaboration
and integration along with improvements in information flow and data processing that
reach beyond the capacity of traditional construction methods (Li et al., 2019).
According to existing literature, Sabet and Chong (2018) listed the leading
capabilities (practices) of BIM as planning and scheduling, constructability assessment,
3-D model visualisation, clash detection, measurement and estimation, site
management, safety management and operation management—as last, but not least.
Through these constructive practices, BIM has improved the construction
industry from different perspectives, enabling stockholders to capture and process
information within a project’s various stages. Information transformation optimises the
project procedure, contributing to perfect completion (Azhar, 2011).
Ismail et al. (2018) declared that BIM is not precisely equal to big data.
However, Bilal et al. (2016) claimed that the application of BIM, along with other
advanced techniques and devices for procuring data, aligns with big data’s mission to
flourish within the industry of construction management.
35
3.2.3.3 Augmented reality.
AR is a technique by which captured images can be manipulated in the same
way as they can in reality. In fact, the images can be linked to the real world, occupying
the same spatial dimensions (Azuma et al., 2001).
AR originated from virtual reality (VR), which partially but tangibly creates an
environment wherein the operability of an object can be sensed and practised in real
time to improve human understanding of it (Jiao, 2013). As the high-quality
visualisation of details is very effective for reducing the complexity of information
(Bilal, 2016), it is claimed that the AR technique accords with big data’s objective to
generate information for better decision-making (Olshannikova et al., 2015). For
example, AR is capable of being paired with BIM to enable designers to apply more
maintainable and sustainable principles to their designs. This point improves facility
management at the building operation stage (Khalek et al., 2019).
3.2.3.4 VR.
VR is a technique via which users can experience the real working environment
before project completion. This technique offers an ‘interactive 3D graphic, user
interfaces, and visual simulation’ (Zyda, 2005, p.25). It has been found to be very useful
for improving safety. VR training significantly improves the efficiency and productivity
of ‘stone cladding work and cast-in-situ concrete work’, saving the time that would be
spent on conventional training (Sacks et al., 2013). They stated that training via VR
effectively attracts newcomers’ attention and produces concision. Messner et al. (2003)
believed that VR helps trainees to understand certain technical details better. The
trainees sensibly address ‘construction sequences, temporary facility locations, trade
coordination, safety issue identification, and design improvements for constructability’
(Messner et al., 2003, p.1).
36
3.2.3.5 Blockchain.
Crosby et al. (2016) defined blockchain as a technique through which not only
the databases of records but also all transactions or digital activities are recorded and
distributed among stockholders. Once entered, data never can be removed. Belle, (2017,
p.280) expressed four characteristics of the blockchain:
(1) It is public, not owned by anybody, (2) it is decentral, not stored on one
single computer but on many computers owned by different people across the world, (3)
constantly synchronised to keep the transactions up to date, and (4) secured by
cryptography to make it tamper proof and hacker proof.
Turk and Klinc (2017) found blockchains to be capable of improving the
construction industry by overcoming lost data and manipulating issues within the life-
cycles of projects. ‘Smart construction relies on BIM for manipulating information
flow, data flow, and management flow’ (Zheng, 2019, p.1), which the blockchain can
address. The processes of unifying data, maintaining verifiable records and keeping data
permanently available make the blockchain relevant to both financial and non-financial
schemes (Crosbey et al., 2016) When it comes to the field of construction, the
application of a blockchain to a smart contract is a bold move (Zheng et al., 2019). A
blockchain can keep an accurate visible history of the actions users have taken across
the network (Pilkington, 2016) thereby supporting the smart contract to be secured. All
provisions and protocols can be permanently available in a chained structure, with no
opportunity of change (Turk& Klinc, 2017). In such a situation, not only can all
regulations be supervised, but the duties of users can also be tracked.
3.2.3.6 Laser scanning.
Laser scanning is a technique by which actual, accurate data from an as-built
situation are retrieved by scanning the work’s progress or status. The data can then be
37
used to evaluate quantities of work and to report progress (El-Omari &Moselhi, 2008)
or for decision-making purposes (Goedert & Meadati, 2008). El-Omari and Moselhi
(2008) believed that the accurate reporting of progress to management is a determinant
action in the effective delivery of projects. The chance of a proper report is higher
through 3D laser scanning, which is capable of highly accurate reporting through the
provision of precise data. Su et al. (2006) observed this technique to be very practical
for improving the efficiency of urban underground works, where working spaces were
restricted in terms of visibility and movement. Randall (2011) described laser scanning
as a complementary measure for BIM that could influence the various phases of
projects, including programming, planning, design, construction, operation and
maintenance.
3.2.3.7 Artificial intelligence techniques.
In simple words, AIs are techniques whereby human perceptions can be
transferred to machines, allowing them to perform the way humans supposedly would in
complicated situations (Chen et al., 2008). AI makes industries more efficient and
effective, allowing intelligent automatic machines to ‘analyse the human’s thinking
system and reflect the same to reality’ (Dede et al., 2019, p.1). This technique enables
automatic machines to mimic human behaviours and operate intelligently (Nau, 2009).
Further, AI can refer to smart software, facilitating better technical information,
management and collaboration fields (Anumba et al., 2002). Therefore, the software
directing robotic machinery can also be considered AI. Bose (2018) discussed three
main areas in which revolutionary AI has intervened. These areas are (1) quicker and
more confident decision-making, (2) immediate accessibility and practical insights
originating from big data and (3) protection of susceptible data.
38
AIs have the potential to rapidly and imminently affect the construction industry
by tackling industrial issues without physically involving humans in a complex working
system (Joes et al., 2018). Joes et al. (2018) listed a range of potential fields within the
construction industry that AIs could influence, including cost overrun, design
optimisation, risk mitigation, planning, site productivity, safety, labour shortages,
prefabrication, data generation and building operation.
3.2.3.8 Off-site manufacture (OSM).
OSM is a technique offering a combination of prefabricated components and on-
site activities. The components are either erected to shape a constructed object or
attached to in-situ built components (Blismas &R. Wakefield, 2009). In fact, ‘the off-
site components are produced in a controlled manufacture environment and then
transported and positioned onto a construction site’ (Sabet& Chong, 2019, p.207). In
2017, the Sustainable Built Environment’s National Research Centre (SBEnrc) declared
that OSM was capable of providing the construction industry with optimal opportunities
over the next decade. These opportunities are significantly aligned with demands for
affordable housing, set to double by 2021. Sabet and Chong (2018) listed a range of
OSM attributes arising from these opportunities: automation and series production,
faster investment return, employment opportunities, sustainability and safety.
3.2.3.9 Automation.
Automation refers to a technique by which a procedure or a cycle of processes is
carried out with minimal human involvement (Groover, 2014). This technique makes
industries more efficient and effective by applying software and hardware to complete
tasks automatically. Through this highly beneficial technique, equipment, machinery
and processes are operated via controlling systems in complex situations. However,
sometimes, a controlling system fails as a consequence of human-related error and any
39
potential benefit is transformed into a loss or even a disaster (Lee& See, 2004). Lee and
See (2004) believed that automation dramatically improves human performance and
safety, provided that accurate data are entered into the system and its transformation is
reliable. Automation has not only been observed to optimise construction site
productivity but is also capable of promoting the mass production of prefabricated
construction components in factories (Neelamkavil, 2009).
3.2.4 Productivity indicators.
Clear objectives are necessary to drive a dramatic improvement in productivity.
These must be followed by constructive strategies, milestones and the identification of
productivity indicators (Force, 1998). These indicators must reflect project inputs and
contribute to project progress as process outputs. Productivity is ‘a relationship (usually
a ratio or an index) between output (goods and/or services) produced by a given
organisational system and quantities of input (resources) utilized by the system to
produce that output’ (Hannula, 2002, p. 59). Force (1998) believes that productivity
indicators must be related to time, cost, quality and predictability.
Sabet and Chong (2019, p.4) explained that ‘input refers to materials ($),
personnel (P-H), and equipment ($) put into the projects while output refers to
production unit’. Construction progress can be simulated for the production unit on
construction sites. Construction activities are ranked as high cost business activities.
Thus, productivity achievement refers to the minimum input needed to achieve a
reasonable output (Huang et al., 2009). In the current paper, the terms productivity and
performance and their borders within the construction field have been discussed as a
preliminary to identification of productivity indicators. “Performance perspective from a
broad sense can be followed by productivity perspective in a narrow sense” (Sabet &
Chong, 2019, p.4). This claim suggests that productivity can be deemed a consequence
40
of performance. However, Dozzi and AbouRizk (1993) stated that the term productivity
equals performance.
Various indicators of productivity and performance have been reported. Socio-
economic conditions have been identified as the reason for this variety across different
countries (Hassan et al., 2018). The indicators have been divided into quantitative and
qualitative categories; quantitative indicators can be physically measured (numerical)
using measurement scales. For example, these indicators might be scaled via a report on
costs, material usage, completion of a proportion of activities and the number of crew
members. Qualitative indicators refer to those that cannot be tangibly observed and
scaled. These indicators do not show the exact data for a project trend but offer a
description of a situation (e.g., a safety report) (Cox et al., 2003). Sabet and Chong
(2019) offered a comprehensive conceptual framework that categorised KPrIs as
company characteristics, labour, materials, management, documentation and
regulations, machinery, contract conditions, IT involvement, engineering and external
circumstances. Among other indicators, improved productivity is guaranteed by an
appropriate management style (Enshassi & Burgess, 1991; Fellows, & Liu, 2012) and
the implementation of well-structured techniques (Winch, 1998).
3.3 Methodology
For this scoping review, a micro-to-macro method was used to assemble the
relevant literature. Each dimension of this two-dimensional view interacts with the other
for a more efficient analysis (Wagner &Derryberry, 1998) of the requirements for the
development and application of advanced techniques. Here, the micro dimension
examines the range of productivity fundamentals as the supplementary foundation on
which advanced techniques should be applied, while the macro dimension focuses on
the stages at which these fundamentals need to be applied. Further, a holistic
41
understanding of the selected advanced techniques is provided through the literature
review. This review method links evidence retrieved from the literature to justify the
designated objectives. This method is particularly relevant in the case of new topics on
which the literature is scarce (Sabet & Chong, 2019). Table 3.2 shows the sources
reviewed to evident this paper’s claim. Also Figure 3.1 shows how the review method
was developed in this study.
Table 3.2 The supportive sources for this paper
NO The sources of the current
paper
The sources contributing
to Productive
fundamentals
The sources confirming advanced
technique definition and their
applications for performance
1 W. He & Y. Shi (2019) X
2 M. Stevens (2014) X
3 L. Sveikauskas et al. (2016) X
4 B. Green (2016) X
5 M. Bronte-Stewart (2015) X X
6 P. Sabet, H.Y. Chong,
(2018)
X X
7 D. McGeorge & PXW. Zou
(2012)
X
8 S. Changali et al. (2015) X
9 D. Richardson (2014) X
10 M. Bresnen & N. Marshall,
(2000)
X
11 S. Ganesan, (1984)
12 T.Force (1998) X
13 G. Winch (1998) X
14 A. Enshassi, & R. Burgess,
(1991)
X
15 R. Fellows, & A. M. Liu,
(2012)
X
16 H.S. Park, (2006) X
17 H.A. Bassioni et al. (2004) X
18 M. Abd El-Razek et al.
(2008)
X
19 N. Azhar et al. (2008) X
20 S. Durdyev & S. Ismail,
(2016)
X
21 S. G. Naoum, (2016) X
42
NO The sources of the current
paper
The sources contributing
to Productive
fundamentals
The sources confirming advanced
technique definition and their
applications for performance
22 S. Emmitt & C. Gorse,
(2006)
X
23 X. Meng, (2012) X
24 S. D. Lavender, (2014) X
25 A. Kazaz & S. Ulubeyli,
(2007)
X
26 A. M. Jarkas & M.
Radosavljevic, (2012)
X
27 N. Jaffar et al. (2011) X
28 I. Shohet & A. Laufer,
(1991)
X
29 M. A. Islam, & M.
Khadem, (2013)
X
30 A. M. Jarkas & C. G. Bitar,
(2011)
X
31 R. F. Aziz & S. M. Hafez,
(2013)
X
32 A. Mills, (2001) X
33 S. Q. Wang et al. (2004) X
34 S. P. Singh, (2010) X
35 S. Alwi, (2003) X
36 P. Ghoddousi & M. R.
Hosseini, (2012)
X
37 H. R. Thomas et al. (2003) X
38 M. Abrey & J. Smallwood,
(2014)
X
39 A. Hanna & D. G. Heale,
(1994)
X
40 E. D. Wagner & A. P.
Derryberry, (1998)
X
41 D. Samson, & M.
Terziovski, (1999)
X
42 A. Jafari & P. E. Love,
(2013)
X
43 Jepsen and Eskerod (2009) X
44 Song et al. (2017) X
45 Nam et al. (2019) X
46 E. Agazzi, (1998) X
47 Isman (2012) X
48 Nguyen & Akhavian (2019) X
49 Gunasekaran & Cecille
(1998)
X
43
NO The sources of the current
paper
The sources contributing
to Productive
fundamentals
The sources confirming advanced
technique definition and their
applications for performance
50 S. A. Ismail, S. Bandi, & Z.
N. Maaz, (2018)
X
51 M. Bilal et al. (2016) X
52 Shrestha (2013) X
53 Motawa (2017) X
54 R. Eadie et al. (2013) X
55 Li et al. (2019) X
56 S. Azhar (2011) X
57 R. Azuma et al. (2001) X
58 Jiao et al. (2013) X
59 Olshannikova et al. (2015) X
60 Khalek et al. (2019) X
61 M. Zyda (2005) X
62 R. Sacks et al. (2013) X
63 J. I. Messner et al. (2003) X
64 M. Crosby et al. (2016) X
65 I. Belle (2017) X
66 Z. Turk & R. Klinc (2017) X
67 R. Zheng et al. (2019) X
68 M. Pilkington, (2016) X
69 S. El-Omari & O. Moselhi,
(2008)
X
70 J. D. Goedert & P. Meadati,
(2008)
X
71 S. El-Omari & O. Moselhi,
(2011)
X X
72 Su et al. (2006) X
73 Randall (2011) X
74 S. H. Chen et al. (2008) X
75 Dede et al. (2019) X
76 D.S. Nau (2009) X
77 C. Anumba et al. (2002) X
78 S. Bose, (2018) X
79 Jose et al. (2018) X
80 N. Blismas &R. Wakefield,
(2009)
X
81 Sabet & Chong (2019) X X
82 SBEnrc (2017) X
83 M.P. Groover (2014) X
44
NO The sources of the current
paper
The sources contributing
to Productive
fundamentals
The sources confirming advanced
technique definition and their
applications for performance
84 J.D. Lee & K. A. See
(2004)
X
85 J. Neelamkavil (2009) X
86 M. Hannula (2002) X
87 A. L. Huang et al. (2009) X
88 S. P. Dozzi, & S. M.
AbouRizk, (1993)
X
89 A. Hasan et al. (2018) X
90 R. F. Cox et al. (2003) X
91 S. Golnaraghi et al. (2019) X
92 H. Elnaas et al. (2014) X
93 J. Lessing et al. (2005) X
94 C. L. Pasquire & Connolly
(2002)
X
95 S. Durdyev, & S. Ismail,
(2019)
X
96 L. Ding et al. (2014) X
97 Kang et al. (2007) X
98 J. Li et al. (2014) X
99 N. Lee et al. (2014) X
100 L. Chen & H. Luo, (2014) X
101 S. Khoshnava et al. (2012) X
102 K. Sulankivi et al. (2010) X
103 X. Wang & P.E. Love
(2012)
X
104 P. Smith (2014) X
105 X. Li et al. (2018) X
106 J. Wong et al. (2014) X
107 A. Behzadi, (2016) X
108 W. Shen et al. (2010) X
109 Z. Pan et al. (2006) X
110 D. Zhao & J. Lucas (2015) X
111 Y. Fang et al. (2014) X
112 R. Oudshoorn (2018) X
113 D. Gleason (2013) X
114 D. Huber et al. (2010) X
115 D. Tapscott &A. Tapscott
( 2017)
X
116 M. Kassem et al.(2018) X
45
NO The sources of the current
paper
The sources contributing
to Productive
fundamentals
The sources confirming advanced
technique definition and their
applications for performance
117 W. Lu et al. (2015) X
118 J. Brandenburger et al.
(2016)
X
119 S. F. Wamba, S. Akter, &
M. De Bourmont, (2019)
X
120 A.Ø. Sørensen, N. Olsson,
and A.D. Landmark, (2016)
X
121 C. Balaguer & M.
Abderrahim, (2008)
X
122 T. Hegazy et al. (1999) X
123 A. O. Elfaki et al. (2014) X
124 J. Peleska (1996) X
125 P. X. Zou et al. (2007) X
126 P. Meadati (2009) X
127 Y. Ji et al (2019) X
128 A. T. Gurmu & C. S.
Ongkowijoyo, (2020)
X
46
Step 1: Clarification of the scope
Aim: To develop an integrated framework for applying a range of
productivity fundamentals to increase the capacity of advanced
techniques to deliver the expected improvements in productivity
Key categories of Investigation
No Categories
Productivity and
performance-related
publications
New technique-
related publications
1 Resources Did the papers address
the roots of poor
productivity and how to
achieve the relevant
aspects of performance?
Did the papers
discuss how new
techniques affect
construction?
2 Management
3 Engineering
4
Innovation
and new
techniques
Step 2: Searching for relevant documents
Stages Resources Key words
Collection
Filtration
Through Google
Scholar and
scientific
databases
Construction
productivity/performance
Advanced techniques in
construction
Productive fundamentals
Productivity indicators
(KPrIs)
Step 3: Analysis of the findings
Step 4: Categorisation of the productivity fundamentals and the
project stages at which they should be implemented
Step 5: Develop a framework to conceptualise the integration of the
productivity fundamentals and the implementation of advanced techniques
Figure 3.1. The procedures used in the scoping review.
The first step was to identify the root causes of poor productivity in the
construction industry. Recent advanced techniques that affect project operating systems
were examined to establish the pathways through which the different aspects of
performance can be improved. To this end, the areas of resources, management,
engineering and innovation were searched. The next stage involved finding relevant
sources by collecting and filtering documents to retrieve credible evidence to
47
substantiate the arguments made in this paper. Documents were identified by searching
Google Scholar and scientific databases using keywords, including ‘construction project
stages’, ‘construction productivity’, ‘construction performance’, ‘advanced techniques
in construction’ and ‘productivity considerations’. Next, the abstracts of the articles
identified scanned to assess the relevance of the paper, and those of interest were
evaluated to develop a clear understanding of the issues and requirements for
construction productivity, productivity fundamentals, the stages at which these
fundamentals should be applied and the capabilities of the relevant advanced
techniques. The research questions were then developed, asking what the state of
construction productivity and performance is, and how to reinforce the implementation
of advanced techniques to fulfil the project objectives and meet the expected return.
3.4 Findings and Data Analysis
The highly dynamic nature of construction projects can be challenging to their
progress (Golnaraghi et al., 2019). Difficult situations can be exacerbated if advanced
techniques are not fundamentally supported in an organised and proper manner to fulfil
their objectives. He and Shi (2019) believed that an ‘effective construction organisation
plan’ is central to a construction optimisation model that results in project performance.
Sabet and Chong (2018) have claimed that the debate around productivity is aligned
with that of performance in the construction industry. They state that the expected
outcome of performance in the boarder sense is achievable through the improvement of
productivity indicators in the narrow sense. This means that performance achievement is
not straightforward, unless the required agents involved in productivity play a vital role
in influencing a project’s work flow.
48
Table 3.3 gives a summary of credible sources indicating how the recent
highlighted advanced techniques have successfully influenced the aspects of
construction performance so far.
Table 3.3 Advanced techniques and their effects on construction projects
Advanced
techniques
Performance
aspects
Ways in which construction projects can be
influenced
Sources
Off-site
manufacture
Time Since better quality control can be achieved in
a more controlled working environment (OSM-
based project), the chance of any rework
disturbing planning and scheduling in a project
is minimised
SBEnrc, 2017;
Elnaas et al.,
2014; Lessing et
al., 2005
Cost 24-hour availability of materials in factory
stock reduces the time needed for ordering and
transferring materials and thus the total project
time.
SBEnrc, 2017;
Pasquire &
Connolly, 2002
Quality Better monitoring of construction processes to
produce the construction elements in a
controlled environment leads to improved
achievement of specifications, which
contributes to quality performance
SBEnrc, 2017;
Lessing et al.,
2005
Safety Safety considerations are easier to observe in a
factory environment where prefabricated
construction components are produced.
Occupational health and safety principles can
efficiently and effectively imposed and
monitored in a controlled work environment
Blismas &
Wakefield, 2009;
SBEnrc, 2017
Stakeholder
satisfaction
Stakeholder satisfaction is achievable by
systematic adoption of advanced techniques.
Respondent satisfaction has been reported for
‘reduced construction periods, on-site
construction and labour costs and improved
quality, there still is room to overweight safety
and waste subjects of OSM-based projects and
compare them with that of non-OSM-based
projects. It is mentionable that the level of
adoption and how the adoption should be
organised can play a determinant role in
stakeholder satisfaction’
Durdyev &
Ismail, 2019, p.1
Building
information
modelling
Time The coincidence of 3-D model of designs in a
virtual environment can reveal any potential
interference between building activities,
limiting the chance of any time-consuming
modifications of initial planning and scheduling
while the project is in progress.
Through a virtual model supported by an
information-sharing platform in BIM, the
parties involved in a project can be linked
Ding et al., 2014;
Kang et al., 2007
49
together to evaluate any potentially conflicting
situations, and a rapid decision can be made in
the case of any confusion that may affect
project progress
Cost Limiting the chance of rework and safety issues
directly influence cost performance. In
addition, a BIM model equipped with planning
and scheduling tools enables the relevant
experts to optimise resource management,
which helps optimise cost performance
Hou et al., 2014
Quality A high-quality virtual model rapidly clarifies
information related to materials specifications
and the delivery details of certain activities,
such as the dispatch and assembly of
prefabricated components at the construction
site. This limits the chance of poor
performance, contributing to improved quality
assurance
Lee et al., 2014
Safety Dynamic safety analysis can be practised via
the virtual site model offered by BIM.
Modelling certain operations, such as cranes
and plants, improves safety management. A
virtual site layout contributes to the effective
management of safety considerations
Chen& Luo,
2014; Khoshnava
et al., 2012;
Sulankivi et al.,
2012
Greater practical clarification is possible by
using a virtual environment to improve
workers’ knowledge, thereby avoiding
potentially hazardous situations
Quality By reviewing the processes involved in certain
activities with the workforce, the chance of
errors or defect in the end product can be
limited
Stakeholder
satisfaction
Easy sharing of information via BIM can
contribute to stakeholder satisfaction as they
can better understand the other parties’ work
scope and processes and coordinate their
activities accordingly, limiting the chance of
potential ambiguities or interference. This
theme optimises multidisciplinary coordination
and provides a better collaborative environment
Chen& Luo,
2014; Wang&
Love, 2012;
Smith, 2014; Li et
al., 2019
Cost The BIM model has excellent capability for
determining measures and estimations of site
activities. Highly accurate estimation could be
offered accordingly, thus reducing excess costs
Cost The optimal operations of cranes and trucks can
be modelled in a BIM, and operators advised
accordingly to achieve efficient performance.
This also optimises the energy resources
necessary to operate the site machinery
efficiently
50
Augmented
reality
Time Time performance is crucial for the
implementation of a site schedule. Visually
monitoring project progress so that as-built
elements can be compared with the as-planned
form of the elements can contribute to optimal
schedule monitoring, improving time
performance.
AR provides practitioners a model of the actual
site in a virtual environment to compare with
the as-built components, which allows quicker
inspections and improves decision-making
processes
Li et al., 2018
Cost AR limits the chance of misinterpreting
drawings and exchanging imprecise data. These
factors are the main source of time and cost
overruns
Wang et al., 2014
Quality AR supports automation, which allows
optimum operation by the user and minimises
defects of operation
Safety An AR system allows practitioners to make
virtual site visits. This can contribute to safety
performance by highlighting any unseen
potential threats without an actual inspection
Stakeholder
satisfaction
Effective communication and information
exchange between the parties involved in the
project contributes to stakeholder satisfaction.
The additional visualisation capability of AR
and the ease of access to information and
sharing information via lightweight devices
improves stakeholder satisfaction
Behzadi, 2016
Virtual reality Time and
cost
Measures such as training the workforce in a
virtual environment and simulating certain
activities related to quality improvement leads
to effective defect management via VR. This
minimises the chance of overlooking any
requirements or specifications consuming,
which can be costly and time-consuming to
rectify
Shen et al., 2010
Quality Machine and equipment operators can be
highly trained before they start work on the
site. The wider workforce can be trained for
certain activities through e-learning in VR. For
example, steel erection and the placement of
installation elements can be modelled in VR.
Therefore, a VR platform can improve the
quality of work
Pan et al., 2006;
Zhao& Lucas,
2015
Safety Training of the workforce is a major concern
before beginning construction. VR provides an
effective platform for training in a virtual
environment
Fang et al., 2014
Stakeholder
satisfaction
Detailed visualisation via VR provides all
parties with a better understanding of the
expectations of others and how to better
cooperate throughout the project. This enables
Oudshroom, 2018
51
a dynamic process for the protection of key
values, openness between parties, and
competitive progress
Laser scanning Time In the absence of information on as-built
elements, laser scanning contributes to
decision-making by offering the information
required for the existing components or
building to plan any changes or renovations
Gleason, 2013;
Huber et al., 2010
Laser scanning offers accurate data for the
production of documentation via capturing and
recording construction progress (as-built
preparation). The risk of the production of
faulty documentation that may offer erroneous
information is limited. The identification of
faults would take time
Goedert &
Meadati, 2008
Quality The data offered by laser scanning can be used
to monitor and evaluate construction progress if
it is in compliance with the specifications as
per the drawings. This contributes to quality
assurance
Gleason, 2013;
Huber et al., 2010
Cost Laser scanning is useful for measuring the
materials required and accurate calculation of
materials orders, limiting the chances of waste
El-Omari &
Moselhi, 2008
Blockchain Stockholder
satisfaction
Modern management encourages the
architecture, engineering and construction
industry to accelerate digitalisation in
architectural and engineering procedures, in
tender and contract ventures and even during
prefabrication for use in construction sites. The
blockchain eliminates any chance of data loss
and manipulation that may necessitate
additional costs through data restoration. Thus,
the potential for disputes among the parties
involved in a project would be limited
Belle, 2017;
Tapscott et al.,
2017
Time and
cost
Quick and reliable access to data and
information is possible by referring to the
decentralised blockchain database. This not
only saves transactional data costs, but also
develops a trusting environment for
collaboration
Kassem et al.,
2018
Big data Time, cost
and
stockholder
satisfaction
Big data-based techniques tangibly affect waste
management optimisation that contributes to
project performance. These techniques
reinforce the reliability of indexes developed
for performance measurement. The waste
management rate as a reliable index is one
example resulting from the application of big
data that has created a benchmark for project
performance in Hong Kong
Lu et al., 2015;
Bilal et al., 2016
Quality Simple and fast access to high resolution data
to monitor quality is an output of big data-
52
mining techniques. Quality can be effectively
tracked by integrating reliable data from
various sources
Brandenburger et
al., 2016; Wamba
et al., 2019;
Sørensen et al.,
2016
Automation
and AI
Time and
cost
A high volume of complicated construction-
related jobs can be successfully accomplished
within a very much shorter period using
automatic robots as hardware and tools.
Further, smart software can be used to optimise
certain processes (e.g., resource allocation and
levelling) and to produce reliable data. The
chance of any errors resulting in delays and
costly reworking is limited by automation.
However, additional costs may be incurred as a
result of its application
Balaguer &
Abderrahim,
2008; Hegazy,
1999
Time and
stockholder
satisfaction
Some AI agents are capable not only of
providing technical information, such as cost
estimation, but also of leveraging collaborative
environments by solving time and distance
issues. In fact, smart software tools provide
stockholders with effective communication
tools
Elfaki et al., 2014;
Anumba et al.,
2002
Safety Complicated procedures and substantial
physical activities create a significant risk of
human error that results in injury. Automation
considerably eliminates situations in which
crew members may become injured
Peleska, 1996
3.5 Integrated Framework
Based on the explanations given in Table 3.3, each technique is able to influence
certain KPrIs only. The uncovered KPrIs appear as devaluing agents for the techniques
to meet the expected productivity improvement. In other words, even though the
productive capabilities of the techniques that can constructively impact the project
productivity, the potential gap contradictory appears that entirely disrupts the
performance achievement.
A range of productivity fundamentals are necessary over the lifecycle of a
project to improve productivity via the implementation of these advanced techniques.
These fundamentals are complementary, and can reinforce the capacity of advanced
techniques to increase productivity. Integration management is essential for the
53
implementation of the essential elements of productivity and advanced technique. A
successful establishment of management relies on close communication between project
participants throughout a project’s lifecycle (He & Shi, 2019). ‘The life cycle of a
construction project is normally divided into a few stages, including conceptual
(feasibility), design, construction, and operation stages’ (Zou et al., 2007, p.6030.
Meadati (2009) includes ‘planning, design, construction, operation and maintenance,
and decommissioning’ in the construction project lifecycle. A range of productivity
fundamentals have been identified in the literature as complementary to the capabilities
of the new advanced techniques. These fundamentals can be potentially be applied
during the concept and design, contracting and procurement, and execution stages of a
construction project (see Table 2.4).
54
Table 3.4 Productivity fundamentals
Productivity fundamentals Relevant project stages
Focus the value of the project only on what is required. Concept and design
Maintain a lifecycle concept of both construction and
operation costs.
Evaluation of alternative scenarios during project planning to
overcome unexpected issues.
Consider site conditions to optimise design.
Involve modular elements and standardisation during the
design.
Stakeholder involvement in the design phase.
Optimisation of engineering procedures.
Share risk between all stakeholders and reflect this in the
contract.
Contracting and procurement
Develop efficient compensation and variation request.
Align the profits of the contractor and the owner as an
incentive for early completion.
Clarify the need for costly items to the owner.
Updating and adjustable planning for micro-plans in case of
overlooked requirements and troubleshooting.
Execution
Employ prefabricated components.
Consider energy saving strategies.
Apply waste minimising strategies.
The integrated framework shown in Figure 3.2 attempts to conceptualise the
productivity fundamentals that need to be applied to support the implementation of
advanced techniques. A range of productivity fundamentals (listed in Table 3. 4) can be
applied throughout at least three stages of a project (concept and design, contracting and
procurement, and execution) once one of the advanced techniques is implemented. To
depict it, Figure 3.2 reflects that productivity indicators can be improved by the
potential capabilities of new advanced techniques that can be reinforced with a range of
productivity fundamentals. The productivity fundamentals and the advanced techniques
directly and indirectly impact the categories of KPrIs, as highlighted in the process
stage in Figure 3.2. The pathways through which the aspects of performance are
55
improved, have been discussed in Table 3.3. Overall, project performance depends on
both practising the fundamentals and the capabilities of the advanced techniques at the
pre-construction and construction stages.
Figure 3.2. Productivity fundamentals to reinforce advanced techniques.
This paper theorises an enriched foundation with a range of productivity
fundamentals that the new advanced techniques can be drawn on. The paper presents a
conceptualisation of a productivity–performance network with the techniques necessary
for achieving reasonable overall project performance, and also addresses the stages at
which these fundamentals can be employed to realise potential improvements.
3.6 Discussion and Conclusion
The call for improved construction productivity implies that efforts toward
improvements in the construction industry have not fulfilled expectations. Exploring
new ways of achieving improvements requires the identification of weaknesses and
strengths, and offering practical strategies that align with the pace of the evolution of
technology. The implementation of advanced techniques in the construction industry is
56
essential for project success (Ji et al., 2019) in such a competitive business world. Aziz
and Hafez (2013) stated that ‘Over the past 40 years’, although several advanced
techniques that contribute to modernisation of the construction, the expected efficiency
level followed by the required productivity have not been satisfied. Advanced
techniques have emerged to satisfy stockholder and end-user demands for productivity.
However, these techniques are not capable of addressing all productivity indicators.
Further, the lack of conditions in which these techniques may flourish diminishes their
capacity. These conditions are referred to as productivity fundamentals in this paper.
Awareness of the productivity fundamentals required to reinforce the implementation of
advanced techniques is necessary for practitioners. Developing new, consistent and
advanced techniques with higher capacities to meet productivity expectations is the
target of construction management. Our micro-to-macro methodology was saturated by
scoping review. The scoping review (Figure 3.1) of 128 credible sources (Table 3.2)
was undertaken to develop a holistic understanding of the productivity requirements in
the construction industry and clarify how the new advanced techniques impact the
broader scale of productivity and performance. Table 3.3 summarises how these
advanced techniques contribute to project operating systems. It highlights that each
technique has its own characteristics that need to be paired with a range of productivity
fundamentals. Higher productivity is dependent on better project operating systems.
What fundamentals, and how to apply them, to improve productivity and achieve better
performance may be a headline in the construction industry. A hundred credible
sources, including journal articles and several industry reports, were analysed to provide
the evidence to substantiate the arguments presented in this paper. This research
highlighted the root causes of poor productivity (Table 3.1). The contributions of the
common advanced techniques to project performance were summarised (Table 3.3),
57
followed by a range of productivity fundamentals (Table 3.4). Finally, a conceptual
framework (Figure 3.2) to conceptualise how to equip a new advanced technique to
maximise their influences on project performance. It was shown that the KPrIs
categories could be merged into the aspects of performance (See Process section in
Figure 3.2). Section 1 shows that the advanced techniques need to be supported by
productivity fundamentals. Applying these techniques, along with the productivity
fundamentals is key to improve operating system for overall performance. The potential
for successful implementation refers to the pathways outlined in this paper supported by
productivity fundamentals. Thus, by offering a more analytical perspective, this paper
has addressed the range of productivity fundamentals that operate throughout all three
stages of a project: concept and design, contracting and procurement, and execution.
The construction industry would dramatically benefit from new advanced techniques
that are based on the productivity fundamental categories. Figure 3.2 conceptualised
performance achievement at the pre-construction and construction stages through the
range of fundamentals that can be integrated to practice these techniques. Further
investigation to highlight the degree of impact of the productivity fundamentals in an
empirical study is recommended.
3.7 Limitations of the Research
The role of qualified craft/ skilled workforce availability that lies in labour
productivity (Richardsone, 2014; Sveikauskas et al., 2016) as well as the management
style of them (Gurmu & Ongkowijoyo, 2020) are inseparable from the construction
productivity theme. The role of newly emerged techniques and the adopted appropriate
technique are the other drivers that affect construction productivity. The scope of this
paper focuses on the role of newly emerged techniques in the productivity only, which
excludes the aspect of workforce availability.
58
Chapter 4: A Conceptual Hybrid OSM–BIM Framework to
Improve Construction Project Performance
Pejman Ghasemi Poor Sabet1; Heap-Yih Chong2
1School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia,
2 School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia.
E-mails: [email protected]; [email protected]
Abstract
Performance improvement has always been an important agenda in the construction
industry. Newly emerged concepts such as off-site manufacturing (OSM) and Building
Information Modelling (BIM) have been revolutionary movements in the construction
industry. However, these methods have not yet fulfilled their full potential, in practice.
These techniques can be independently applied in construction projects, but their
integrated application would contribute to the fulfilment of their potential to truly
benefit the industry. Hence, a new hybrid OSM–BIM system (HOBS) is proposed for
performance improvement. This paper aims to review the current state of BIM and
OSM techniques to conceptualise a hybrid OSM–BIM framework that formulates their
potential interactions and enhances performance in construction projects. An extensive
literature review will be conducted to meet the following objectives: (a) to highlight
construction performance variables as the targets to be affected by the two techniques;
(b) to discuss the standalone attributes of each technique that contribute to the overall
project performance. The overall performance is considered because the constructive
59
capabilities and attributes can support and equip a project from in conception level to
the construction level. The current paper is expected to not only lay the foundation for
exploring interactions to improve the performance of this system through planning and
managerial stages, but to also provide solid evidence to encourage professionals and
project owners to adopt it. Therefore, client demand will increase, which is vital to the
deployment of the system in the construction industry.
Keywords: OSM and BIM framework, OSM capabilities, BIM capabilities,
OSM and BIM interactions, construction performance.
60
4.1 Introduction
Fragmentation in construction projects has been recognised as the root of
inefficiency. The need for the resolution of these inefficiencies has paved the way for
the emergence of information technologies (ITs). The construction industry has
experienced three eras in IT: computerised drafting, electronic and internet contacting
tools and techniques and tools integration (Arnold & Javernick-Will, 2012). In recent
decades, professionals and authorities have strongly focused on improving data sharing
and collaboration among project stockholders with IT (Zhu & Augenbroe, 2006).
However, the individual adoption of IT techniques has not met the expected
productivity and performance level of projects in response to the high demand of
housing. The market is still calling out for productivity and performance. Along with
using new IT applications, some researchers recommended taking a different point of
view and argue for the integration of other value-making considerations and concepts,
through IT(Ahmad, Russell, & Abou-Zeid, 1995).This integration focuses on fulfilling
and supplementing IT; for example, linking stockholders and crews, in addition to
accelerating the achievement of other concepts (Segerstedt & Olofsson, 2010). Building
information modelling (BIM) and off-site manufacturing (OSM) are the new techniques
that have attracted researchers’ attention. It has been suggested that these two
techniques are capable of supplementing each other to improve the construction
industry (Abanda, Tah, & Cheung, 2017). The limited literature in this area encourages
more research on the deal between OSM and BIM. There are a limited number of
studies discussing the potential contribution of the two techniques.
This article aims to investigate the standalone attributes of the two techniques,
from the view of project performance, to propose a method for identifying potential
potential interactions between the two techniques. The observation and evaluation of
61
other aspects of new achievements can reveal evidence of practicality, which can
encourage the users to adopt the technology. This is particularly useful in the
construction industry, which is resistant to change. The current paper is based on the
following questions: ‘What are the capabilities supporting the successful establishment
of a hybrid OSM–BIM system?’; ‘To what extent do those capabilities satisfy the
aspects of overall project performance?’; and ‘What are the barriers against the
successful establishment of the system?’ Therefore, this paper hypothesises that some
capabilities of the two techniques overlap to supplement each other. Figure 4.1 shows
the overall hypothesis.
Figure 4.1. The general feature of the hypothesis.
This paper is a part of larger research to develop a pathway that leads to
practical interactions and the systematic adoption of this new system for future OSM
construction projects.
4.2 Scoping Review
Three scopes, namely BIM, OSM and performance in construction, were
considered to gather the information required for the study. The keywords used to
search the articles were ‘building information modelling’, ‘off-site manufacture’,
‘performance in construction’ and ‘potential BIM/OSM interactions’. The questions by
which the papers were selected were ‘Did the paper address BIM capabilities and OSM
62
attributes?’; ‘Did the paper discuss its implementation?’; ‘What are the aspects of
project performance in the construction industry and how are the aspects achieved
through OSM and BIM?’ If the abstract of the paper generally answered each question
at a glance, then the paper was selected to review in detail. The authors sought to
potentially bridge and pair up the two techniques for a concurrent application. This
paper is a foundation to hypothesise and address the potential interactions between
OSM and BIM and examine them for practicability. The examination will be followed
by structural equation modelling (SEM) and social network analysis.
4.3 Background
4.3.1 Project performance variables.
The need for performance followed by profit margins has caused new
technologies to emerge in recent years, though the construction industry has resisted
their adoption and slowed steps towards the adoption of alternative techniques. The
dynamic and challenging nature of construction projects results in inefficiencies within
projects, owing to complicated communication lines, complicated processes, large
volumes of detailed data and a lack of practical and effective integration of stockholders
(Holt, 2015). The industry requires well-functioning systems to meet the expected level
of performance. A system is referred to a set of interactions or interdependent
substances that shape a united whole (McNamara, 2006). McNarama (2006) clarified
that ‘the system has various inputs, which go through certain processes to produce
certain outputs, which together, accomplish the overall desired goal’ (p. 140).
Therefore, to address shortages in housing supply more effectively, builders attempt to
find more efficient methods for constructing homes by means of novel materials and
innovative construction methods (Mostafa, Dumrak, Chileshe, & Zuo, 2014).
63
Jha and Iyer (2006) categorised project performance criteria as time, cost,
quality, safety and ‘no-dispute’ (see Figure 4.2). The variable of no-dispute is rooted in
stockholders’ satisfaction. Gunathilaka, Tuuli and Dainty (2013) added more variables,
namely technical performance, planning performance, user satisfaction and
productivity/efficiency—they considered these the criteria for project success.
Figure 4.2. The variables of project performance.
4.3.1.1 Budget performance.
Budget (or cost) performance refers to compliance with the estimated budget for
a project. It occurs when the total expenses of a completed project do not exceed the
estimation. It is a quantitative performance indicator, which is measurable in
construction projects (Cho, Hong, & Hyun, 2009).
4.3.1.2 Time performance.
Time performance refers to observing the time baseline in accordance with the
initial schedule of projects. This variable is set to avoid project time overrun and
extension for project completion. This is a quantitative performance indicator in
construction projects (Cho et al., 2009).
Overall project performance
No-dispute (stackholders' satisfaction)
Quality performance
Time performance
Cost (budget) performance
Safety performance
64
4.3.1.3 Quality performance.
Quality performance is achieved when all specifications comply with the
required quality standards. Cho et al. (2009) highlighted that quality performance is not
measurable, but it is evaluable as a qualitative performance indicator.
4.3.1.4 Safety performance.
This indicator refers to the adherence to reasonable safety considerations to
control possible risks to avoid or lower the chances of any incidents or damage
(Nevhage & Lindahl, 2008) within an organisation, including construction
organisations.
4.3.1.5 Stockholder satisfaction.
Stockholder satisfaction refers to stockholders’ expectations regarding receiving
a program or product that covers their needs and interests (Susnienė & Vanagas, 2007).
To be more specific, stockholder satisfaction refers to compliance with serviceability, in
which, every party’s expectations of the other project participants are observed.
Expectations may be any required, operational contribution that the other parties must
make so that the project can progress. Each stockholder plays an effective and
contributing role to the results of a project.
Essentially, to meet project performance indicators, new technologies have
emerged to simplify process complexity, which could be the root of the issue. Among
the new technologies, BIM and OSM have gained considerable reputations. Once the
techniques were in practice, various countries reported various degrees of benefits—in
such a way as to preclude a general consensus.
Therefore, how the techniques are practised is vital to achieving an acceptable
result. As far as OSM is concerned, the possible inconsistencies between manufacturing
65
and construction contractors’ activities can exacerbate the inefficiencies in construction
sites.
4.3.2 OSM.
Most companies in the construction industry are experiencing a pressing need to
enhance their productivity to properly satisfy current demands in the housing sector.
Pan and Sidwell (2011) claimed that the increase in demand for housing, in the British
context, has caused the industry to consider the use of alternatives to building systems
to accomplish the housing projects in an efficient way.
OSM is a modern technique, in which components are constructed off-site and
then attached to on-site activities. The off-site components are produced in a controlled
manufacturing environment, then transported to, and positioned in, a construction site
(Blismas, 2007). OSM has demonstrated the capacity for producing high volume and
high-quality residential buildings on the basis of manufacturing principles (Manley,
McFallan, & Kajewski, 2009; Li et al., 2014). According to Blismas and Wakefield
(2009), OSM can effectively boost the supply of housing. A common, key suggestion in
all reports noted above is the need to adopt the ‘factory production’ style methods in the
construction industry, for the purpose of enhancing the efficiency of this sector with
manufacturing processes. Additionally, new strategies and targets have been set by the
British government and industry sector, which aim to transform the construction
industry by 2025, in regards to the achievement of faster delivery, lower costs, lower
emissions and improved exports. The house-building sector has attempted to review the
operations carried out in this sector and has sought new approaches to improving the
ways that new housing projects are delivered. Thuesen and Hvam (2011) stated that the
construction industry was experiencing continual pressure to enhance its productivity,
decrease costs, enhance quality, improve sustainability and minimise health and safety
66
risks. Such pressures have caused a big dilemma that cannot be resolved without a
fundamental change in the delivery of house-building projects. As a result, it is
necessary to achieve a deeper understanding of the potentials of applying OSM to the
construction industry and also to determine the most significant measures that must be
taken to optimise the application of OSM in the house-building sector.
4.3.2.1 Standalone potential capabilities of OSM.
The resistance to change in construction means that researchers must argue the
potential benefits of OSM. Ismail et al. (2012) believed that the three most influential
factors related to management comprised ‘good collaboration, effective communication
channel and team member involvement’ (p.99), and that these factors could play leading
roles in the successful adoption of the new techniques in future projects. The adoption
of OSM has significantly increased, as OSM has been identified as a technique to
reduce the duration of housing projects. This technique has contributed to ambitious
improvements in productivity in the Singaporean housing market (Gao, Low, & Nair,
2018). Hamid and Kamar (2012) discussed construction time saving as one achievement
of the OSM technique. Hu et al. (2019) found the shorter project duration to be a
perceived benefit of OSM. The status of OSM in Malaysia is different. Although the
quality of OSM-based housing has been better than that of more traditional housing,
some factors such as ‘lack of experience, poor communication, financial problems, and
restrictions by stakeholders’ (Hu et al., 2019, p.8) have remained as barriers to the
application of OSM. Gao et al. (2018) stated that the lack of a push factor for authorities
is a potential barrier to OSM technique implementation in Malaysia. The Chinese
government has recognised the optimisations of time, cost and quality through the OSM
technique. OSM has been mandated in some jurisdictions and is expected to account for
30% of China’s total construction in the next decade. However, China has been
67
struggling with a lack of regulation and standards to extend the application of OSM
(Gan et al., 2018).
The Sustainable Built Environment National Research Centre (SBEnrc) in
Australia believes that OSM could offer great opportunities to the construction industry
in upcoming decades. It predicted that the demand for affordable housing would double
by 2021, compared with 2012. Thus, studies that consider responding to the demand
and satisfying time, cost and quality criteria are necessary. SBEnrc also reported that the
UK, as a pioneer in fostering and taking advantage of OSM, had a noticeable
improvement in its housing program. This means that significant environmental,
economic and social benefits have been achieved via OSM (SBEnrc, 2015). Figure 4.3
illustrates the main, potential capabilities of OSM.
Figure 4.3. General OSM capabilities.
Automation and series production.
The optimisation of time, cost and quality in the construction industry has often
been proposed through automation and series production in the factory environment
where the construction components are made (Duc, Forsythe, & Orr, 2014). Products
General OSMcapabilities
Automation/Series
production
Safety considerations
Sustainability considerations
Employment opportunities
Faster investment
return
68
are made in a controlled manufacturing environment in such a way that the activities are
heavily centralised. Thus, the foundation for the use of automated machinery is
indirectly provided on the construction site. Automated, off-site manufacture has been
recognised as having more potential revenue through mass customisation (Benros &
Duarte, 2009) compared with non-automated OSM. Not only have the aspects of time,
cost and quality been observed, but safety satisfaction has also been achieved through
automation.
Faster investment return.
Mostafa et al. (2014) believe that ‘The economic-related factors such as
consumer price index, changes in the interest and inflation rates are the key driving
factors to the demand and supply of houses’(p.64). Dormant capital, trapped investment
and longer investment return are the issues that significantly affect the earlier mentioned
factors. As OSM can shorten project completion time (Goulding, Pour Rahimian, Arif,
& Sharp, 2015), it is predicted that OSM can overcome these kinds of increases in final
cost issues. Therefore, the project would be more attractive to the buyers, as the final
cost would be competitive. This highlights faster investment return for the investors
(SBEnrc, 2015).
Employment opportunities.
It is observed that off-site component production and its business-related
activities in the United States fostered the growth of employment opportunities
(Eastman & Sacks, 2008), along with other potential benefits. OSM offers steady, long-
term job opportunities in factory-based employment, even in remote regions (Arif,
Goulding, & Rahimian, 2012; Blismas, 2007).
69
Sustainability.
The manufactured components of buildings can contribute to the resolution of
time, budget and quality inefficiencies. Therefore, there is a belief that OSM bettered
sustainability by reducing waste (Duc et al., 2014). OSM, as an end-user value achiever,
can be deemed a remarkable contributor to sustainability via satisfying both lean and
agile concepts (Mostafa et al., 2014). Mostafa et al. (2014) also highlighted that the key
point of the lean technique is waste elimination, while agile focuses on market
satisfaction. It is observed that the ultimate price of the final production for end users
(those who use the product, e.g. home occupiers) would be more economical than the
production in traditional methods (Eastman & Sacks, 2008).
Therefore, proponents of OSM can claim benefits pertaining to factors including
social (users’ comfort), economic (lower price due to less material consumption and less
project overhead costs) and environmental sustainability (less waste-related outcome).
Safety.
Safety improvement is recognised as a continuous challenge in OSM-based
projects by optimised construction management. It is highlighted that a tidier
construction site results in the betterment of site management (Goulding et al., 2015). In
addition, safety measures for working at heights or lifting and loading materials and
components are much more controllable and applicable in a factory environment. Thus,
better working conditions are provided in factories—resulting in improvements to
health and safety (Nahmens & Ikuma, 2011).
A suitable level of OSM application not only expedites a project as a catalyst but
also makes it economical. An early decision toward OSM-related activities and an
efficient process would eliminate inefficiencies and avoid any disturbance in the project
70
(Gibb, 2001). The uptake level can vary in the project, based on the characteristics and
situation of the project.
4.3.3 BIM.
One of the countries that pioneered rethinking construction is the UK. The
authorities, engineers and researchers in the UK found BIM capable of solving
problems of low productivity and costs overrun in the construction sector (Jonsson &
Rudberg, 2014). BIM is the process of developing and applying a simulated model of
planning, designing, construction and operation of a building. The model contains a
collection of digital data and rich information about all details related to a project,
during its life cycle. The BIM model originated from a smart 3-dimensional CAD which
is automatically adaptable to any change and is connected to a shareable database,
which performs as a common source among parties involved in a project. As there are
different levels of details for a BIM model, sometimes it might be designed for a
building only for visualisation and analysis of safety cases or for the maintenance of the
project (Jung & Joo, 2011). BIM entered the area of architecture, engineering and
management with different levels of uptake (Kim, Park, & Chin, 2016). The level of
BIM uptake is determined by the activities for which BIM is supposed to be used for.
This theme determines the level of practices, integration and the professional level of
the companies in BIM application in different countries. Thus, the uptake level varies
from one company to another (Haron, Marshall-Ponting, & Aouad, 2010; Newton &
Chileshe, 2012). Chong, Lopez, Wang, Wang and Zhao (2016) conducted a case study
claiming that the cultural and managerial aspects allow for a progressive BIM adoption
in Australia and China. Almost seven dimensions of BIM can be considered, from
visualisation to facility management for this adoption (Kim et al., 2016).
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4.3.3.1 Standalone capabilities of BIM.
It can be stated that a BIM full package contains various tools—each tool with
its own practicability in different schemes within a project. A BIM package can be
imagined as a general tool kit containing different tools. A wrench, as a tool in a BIM
package, can tighten a nut. Structural components need to be attached to one to erect the
steel structure (steel skeleton) of a building. In this regard, the wrench can tighten the
nuts to keep the stability of the structure, which refers to the technical performance of
the structure. As reflected in research by Chong, Lee and Wang (2017), Olatunji (2012)
and Beveridge (2012), Figure 4.4 presents eight categories as the main BIM capabilities,
which are applicable at different levels of BIM uptake in the project life cycle.
Figure 4.4. Main BIM capabilities/practices.
This unique collection of the constructive capabilities gives BIM the potential
for adoption not only in building but also in infrastructure projects (Chong et al., 2016).
These capabilities even have the potential to lead an efficient and effective contract
administration (Chong, Zin, & Chong, 2012). Chong et al. (2012) prototyped an
electronic dispute resolution (e-DR) that optimises contract administration. They based
BIM capabilities
Facility management
Safety measurments
3D-model
Site Management
Constructability assessment
Clash detection
Planning/ Schedueling
Measurement/ Estimation
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the prototype on a guideline containing all the data of agreements between the experts
involved in a project.
4.3.3.2 3-D modelling.
This capability offers a general volumetric shape of the elements in structural,
architectural and instalments (mechanical and electrical) designs. The perspective of 2-
D drawings is visualised via 3-D modelling. In this model, the completed form of a
building can be observed by the construction team members and the client(s) in a 3-D
environment and they can have a virtual walkthrough before completion of the building.
It visually represents what the building will look like from both external and internal
perspectives (Clevenger, Ozbek, Glick, & Porter, 2010). This is one of the most basic
applications of BIM.
4.3.3.3 Measurement and estimation.
The BIM model makes estimations about project costs on the basis of the
structural components presented in the model. Most of the time, this part is referred to
as a ‘5-D’ option. Quantities are inferred from the model and considered in estimations.
When a new specification is added to the model, the estimation status is accordingly
updated. The client can simply determine and approve the cost of changes occurred to
the primary design (Aibinu & Venkatesh, 2014). Therefore, offering the quantity of
materials with high accuracy and predicting their total cost is possible with a BIM
model.
4.3.3.4 Planning and scheduling.
BIM planning is the ability to develop a digital work breakdown structure
(WBS) which prioritises activities and links them to each other. It can be stated that
sequencing capability lies in planning, while scheduling capability refers to assigning a
duration to the activities (Büchmann-Slorup & Andersson, 2010). Scheduling is a tool
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to add the digital model to the time factor. BIM puts all components of the construction
within a certain timeframe, outlined by the schedule; it allows users to check the project
path towards the end point in an organised manner (König, Koch, Habenicht, &
Spieckermann, 2012).
These capabilities can be followed by the capability of monitoring a project’s
progress, along with the possibility of rescheduling activities.
4.3.3.5 Clash detection.
As a building project comprises numerous components in structural,
architectural, mechanical and electrical designs, the chance of design interference while
the drawings are being interpreted is high. BIM offers chances to detect conflict by
combining the 3-D models of the designs, which is a remarkable capability. In addition,
in case of huge projects, there may appear thousands of situations in need of change,
which finally lead to this type of clash. Contractors claim that they are able now to
remove almost all of them (Beveridge, 2012). This is recognised as a widely used
application of BIM, which is described as low-hanging fruit (Seo, Lee, Kim, & Kim,
2012).
4.3.3.6 Constructability.
Almost all projects involve a stage for creative thinking, during which lots of
ideas are proposed, but not all of them can be accepted. BIM has the capacity to make
this process easier, by simulating the ideas in a way to simply decide if they are
practical and affordable, or not (Tauriainen et al., 2014). Further, A BIM model can be
updated based on every change in the model. This means that the components
automatically adjust themselves to the new state of the model (Farnsworth, Beveridge,
Miller, & Christofferson, 2015). Thus, the assessment of any variation in the outcome is
possible, as BIM is a smart model which reflects constructability.
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4.3.3.7 Site coordination.
Sequence clarification, via a BIM model, gives site coordinators more chances
to recognise the required trades, materials and equipment to prepare the commencement
and execute every construction activity better. Overall, a coordinating office can be
established, where employees can review the model whenever needed, at a specified
place. It can be used in design meetings, in case the whole model or some clashes need
to be reviewed, as well as during the decision-making process (Paranandi, 2015).This
point reflects the ability of site coordination.
4.3.3.8 Safety measurements.
Safety measurements refer to BIM’s capabilities for automated safety
measurement, alerting fall situation from heights and highlighting the best access to the
routs for plant operation—and specifically, offering optimum lifting drawings for crane
operation (Zhang, AlBahnassi, & Hammad, 2010).
4.3.3.9 Facility management.
Facility management refers to the ability to manage the operation of building, in
case there is a need to extract the data of the existing building. A digital BIM model can
be deemed as a foundation for perfect facility management. As an example, knowing
about the in-built components is possible if the removal of a part of a building is
required (Nicał & Wodyński, 2016). The laser scanning ability in BIM can collect
numerous and accurate spatial data of construction progress and store the information
that might be required in any maintenance or renovation situations (Beveridge, 2012).
This ability is vital to conducting the facility effectively and efficiently over its entire
life (Arayici, Onyenobi, & Egbu, 2012).
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4.3.4 Barriers for the development of the hybrid OSM–BIM system.
4.3.4.1 Barriers on the BIM side.
The nominated elements of BIM in Section 4.1, which have been brought from
industry and academia, reflect the constructive applicability of BIM. Although many
influential BIM tools offering the elements have been introduced, the tools alone have
not been sufficient for efficiently implementing BIM. A range of changes are required,
in terms of ‘work practices, staff skills, relation among BIM implementation team, and
contractual arrangement’ (Migilinskas, Popov, Juocevicius, & Ustinovichius, 2013).
Because there is no willingness to adopt BIM beyond mandatory themes (akin to the
UK’s level 2 BIM uptake), it has officially only been partially adopted (Migilinskas et
al., 2013).
4.3.4.2 Barriers on OSM side.
The most common barriers to OSM have been reported to be longer project
durations and the excessive costs of modifications. The relevant excessive costs in
OSM-based projects (costs which are not applicable to non-OSM projects) are assumed
to be the most debatable issues for OSM uptake (Blismas & Wakefield, 2009).
Blismas, Pasquire and Gibb (2006) categorised material, labour and
transportation costs as the most direct and costly exercises, while site facilities, crane
use and rectification of works were taken into account as indirect costs. The costly
items, together with consistent management and safety measures, are the determining
factors of OSM uptake. The literature review determined that the barriers of OSM
projects are fragmentation among participants, high initial capital cost, reluctance of
insurers and financial providers, excessive cost compared with non-OSM projects and
insufficient accurate drawings. Every single barrier negatively affects projects and
potentially hinders the practicability of the techniques. Therefore, as an attempt to
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remove the barriers on both sides (BIM and OSM), it is reasonable to consider the
development of a hybrid OSM–BIM system.
4.4 Discussion
The current study suggests the development of an OSM–BIM system. The
potential supplementary and overlapping capabilities, as the potential OSM–BIM
interactions (POBIs), to enhance project performance has been observed and
highlighted. The great capabilities of the two newly emerged techniques make them
worthwhile to use. However, as discussed in section 3.6, professionals argue about the
applicability of their attributes and capabilities. BIM has been said to possess some
potential to reinforce OSM. It has been claimed that suitable levels of BIM uptake are
capable of resolving the barriers reported in OSM projects, to meet project performance.
Based on the literature provided in the current study, BIM can step in and rectify
the potential barriers encountered in OSM-based projects. Regarding the fragmentation
of participants (designer, manufacture and construction contractors), the nature of
BIM’s information-sharing platform links the participants. The construction industry
will take a determinant step toward project performance once the inefficiencies caused
by the fragmentation issue are removed. BIM can offer the exact specifications to keep
the required quality when producing components, which is an important consideration
from a manufacturer’s perspective. BIM can also address how to merge components to
meet the expected functionality, within the delivery and operation stages. Therefore,
there would not be any chance of hidden functionality failures. What this means is that
the assurance of a reasonable construction delivery encourages the stockholders and the
investors. Further, a perfect feasibility assessment is possible through a systematic,
smart and digital environment of a project. This assessment can be followed by the
accuracy in planning and scheduling, clash detection, measurement and estimation—
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contributing to project performance. This range of offers through BIM trims any
excessive costs and optimises the budget assigned to an OSM project. As a result, a
better initial capital cost may be concluded, which encourages the finance provider.
The current study hypothesised and predicted some constructive interoperability
as interactions between the two techniques. Therefore, this article conceptualised the
claims with the purpose of examining them through an empirical study in the future.
The potential interactions are flagged in Figure 4.5. The figure shows that the
two techniques can tackle barriers and bridge the potential capabilities to achieve a
range of interactions that optimise project performance. The question is how to
conceptualise the interactions. It is also shown that the interactions need to be
systematically applied to fully benefit the projects. Their systematic adoption could be
achieved through questioning how, where and when to implement them, and where the
inbounding points of applying the interactions are within an OSM–BIM-based project.
Therefore, the systematic adoption presented in Figure 4.5 refers to a system through
which all the detected, nominated interactions can be effectively applied in the design
and construction stages.
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Figure 4.5. A conceptual framework to develop a hybrid OSM–BIM system for project
performance.
4.5 Conclusion and Further Research
The scope of this study lies in the fields of BIM, OSM and project performance.
This study conceptualised a framework for a new hybrid OSM–BIM system to enhance
project performance. Through the literature review, the capabilities of BIM and OSM
(See Figures 4.3 and 4.4) and their direct and indirect effects on performance were
discussed, respectively. In addition, the arguments about barriers of each technique were
briefly pointed out in section 3. 3. 4. The potential constructive interactions were
conceived by analysing and evaluating the capabilities and attributes of the techniques
in the consideration of performance. Figure 4.5 suggests that the two techniques are
capable of going beyond the barriers and moving towards a range of potential OSM–
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BIM interactions (POBIs) at the design and construction stages. The design stages refer
to considerations corresponding to the design for manufacture assembly and
construction delivery (the construction site activities). As reflected in Figure 4.5, the
interactions are assumed to be more effective under a systematic adoption. The
systematic adoption can be defined as a system through which the interactions would be
correctly applied at the right time and stages under a collaborative involvement of the
participants. This study is a foundation toward detecting the potential technical
interactions, which needs to be followed by systematic adoption, applicable in planning
and managerial schemes.
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Chapter 5: Potential Interactions Between Building
Information Modelling and Off-Site Manufacturing for
Productivity Improvement
Pejman Ghasemi Poor Sabet1; Heap-Yih Chong2
1School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia,
2 School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia.
E-mails: [email protected]; [email protected]
Abstract
Purpose- New methods have been introduced as revolutionary approaches in the
construction industry, such as off-site manufacturing (OSM) and Building Information
Modelling (BIM). Although these approaches can provide many benefits, there are still
barriers to meeting the expectations of improved construction productivity via their
implementation. Hence, this paper aims to critically review the capabilities of OSM and
BIM techniques, as well as their potential interactions, in productivity improvement.
Design/methodology/approach- A scoping review approach was adopted, where
100 peer-reviewed journal articles were collected to analyse the capabilities of OSM
and BIM, as well as their potential interactions, in productivity improvement as
assessed by key productivity indicators (KPrIs).
Findings- The results reveal seven BIM-based capabilities and six OSM-based
capabilities, as well as 12 potential OSM–BIM interactions that have significant
potential for satisfying KPrIs.
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Originality/value- An integrated framework has also been developed to clarify
and conceptualise the roles of OSM–BIM interactions in their designated KPrIs. The
research has developed insightful and practical references for strategic planning and
management in OSM–BIM-based projects.
Keywords Construction, Project Performance, Productivity, Capabilities,
Integrated Framework, Interactions, OSM, BIM
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5.1 Introduction
Construction professionals have always searched for new methods to improve
productivity. However, the selection of the most suitable and practical construction
method remains a common challenge in construction performance (Ferrada & Serpell,
2013). Traditionally, researchers have attempted to target productivity improvement
through benchmarking the best practices with productivity indicators in construction
projects (Arditi & Mochtar, 2000; Cox, Issa, & Ahrens, 2003; Enshassi, Kochendoerfer,
& Abed, 2013). Achieving success in the establishment of new techniques to acquire
modernised technologies very much depends on the balance of the integration of the
capabilities and potentials of the system against the fragmentation of the processes and
parties involved in a project (Blayse & Manley, 2004). The collaboration of all parties is
key to performance enhancement and successful project delivery (Walker, 2018).
Building Information Modelling (BIM) is a new technique that has recently
arisen in the construction industry worldwide, and operates at different stages of the life
cycle of a project. BIM, through its visualisation and information-sharing abilities,
enables stakeholders to combine designs and assess the outcomes during the early
stages of a project (Ding, Zuo, Wu, & Wang, 2015). Porwal and Hewage (2013)
observed in their case study that BIM has been proven to improve the construction
process through efficient coordination among the stakeholders and the provision of
accurate information. In fact, many countries have actively promoted BIM technology.
The US is believed to be one of the pioneering countries in the adoption of BIM, where
the public sector and departments at different levels have established BIM programmes,
roadmaps and standards (Cheng & Lu, 2015). The United Kingdom (UK) government
has the same approach to BIM and has even regulated the mandatory measure to use of
BIM Level 2 on certain projects (Khosrowshahi & Arayici, 2012; Ganah & John, 2014).
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The mandatory use of BIM could bring increased competitiveness and productivity in
the long run (Bryde et al., 2013). The potential of BIM to increase construction
productivity and performance in the broader sense has been extended from buildings to
infrastructure projects (Chong et al., 2016). The clarification of responsibilities,
agreements and duties through BIM effectively contributes to project productivity
(Azhar, 2011; Chong et al., 2017; Love, et al., 2011). Nevertheless, BIM is still
evolving and its potential very much depends on certain factors, such as project size,
team members’ proficiency, the communication conditions among the project’s
members and external organisation-related factors (Barlish and Sollivan, 2012).
Off-Site Manufacturing (OSM) is a method in which components are produced
via factory activities and then assembled and erected via on-site activities (Khalfan &
Maqsood, 2014). OSM has been defined as a technique for improving both quality and
quantity in construction. OSM consistently demonstrates higher productivity
improvement compared with traditional construction based on on-site activities only
(Eastman & Sacks, 2008). It has also been introduced as the most influential agent in
creating noticeable opportunities to improve the construction industry globally in future
decades (SBEnrc, 2017).
In response to stakeholders and end users’ expectations, the interactions between
these new technologies have put on the agenda to optimise time, cost and quality, as the
main aspects determining construction performance (Aliakbarlou et al., 2018). Although
these new concepts can be applied to projects independently, some characteristics of
each concept will cover the others via hybrid concepts to improve the stages of the
project. For example, BIM is able to supplement certain other new technologies in
achieving their objectives. BIM and lean collaboration has been a widely highlighted
outcome, owing to the integration of these concepts. Fifty-six interactions have been
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identified between BIM and lean collaboration that improve the construction industry
(Sacks et al., 2010). Another research study linked these two techniques under a mutual
mission of waste reduction and efficiency growth, which generally created value in the
construction sector (Bi and Jia, 2016). It has been observed that an enriched model
developed from BIM standards not only creates a platform for exact data exchange,
through an effective communication line promoting lean concepts (Hamdi and Leite,
2012; Sacks et al., 2009), but also improves prefabrication systems (Moghadam et al.,
2012; Nawari, 2012). BIM is perceived to be one of the new technologies capable of
accompanying OSM. BIM specifications seem to confer the ability to support and
complement OSM and fulfil its potential once applied in practice.
Therefore, this paper aims to critically review the capabilities of both the OSM
and BIM techniques, as well as their potential interactions in productivity improvement.
A scoping review was adopted and the pathway was developed based on the question,
‘which productivity indicators have the capacity to be affected to optimise project
progress?’, followed by another question: ‘which indicators could be affected via the
interaction of these two concepts and how do these capabilities overlap or work
individually?’ For this purpose, initially key productivity indicators (KPrIs) need to be
developed through the literature review before investigating the effects of BIM and
OSM on these indicators. This paper summarises how BIM can contribute to the
improvement of project progress in an OSM-based project and vice versa. More
specifically, the capabilities of BIM include highly accurate information regarding the
specifications of components, visualisation of the project and site via a 3D model, a
rapid information-sharing platform for early decision-making and optimum
planning/scheduling, all of which can promote productivity in OSM-based construction
projects.
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5.2 Literature Review
Low productivity on construction sites has always been one of the stakeholders’
main challenges in the construction industry. Many researchers have tried to develop
various ideas to identify effective practices from different concepts and integrate these
to promote the industry’s status. The focus has been on improving customer satisfaction
through product and process development, which required fostering of commitment
between all parties involved in a project (Murray, 2003; Segerstedt and Olofsson, 2010).
As such, KPrIs play a significant role in a construction project.
5.2.1 KPrIs in construction.
Productivity variables in construction projects can be referred to as the variables
by which the actual project progresses as the output will occur and be assessed by
comparing it to the planning and scheduling template. Dozzi and AbouRizk (1993)
stated that ‘traditionally productivity has been defined as the ratio of input/output’ (p.
1). Input refers to materials ($), personnel (P-H), management and equipment ($), while
output refers to the production unit. The high costs of construction projects are in the
nature of these projects. Thus, the minimum input expected to obtain the maximum
output is deemed ‘productivity achievement’ (Huang et al, 2009). In this paper, the
authors attempted to clarify the terms construction ‘performance’ and ‘productivity’.
The authors refer to the performance perspective as a broad overview, which can be
followed by the productivity perspective in a narrow sense. This means that productivity
is aligned with performance. Therefore, the productivity perspective may follow the
performance perspective. However, Dozzi and AbouRizk (1993) believe that the term
‘performance’ can also be used instead of ‘productivity’. Comin (2006) stated that
‘Total Factor Productivity is the portion of output not explained by the number of inputs
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used in production’ (p. 260). Thus, the production unit can be deemed as project
progress in construction projects.
There is a wide range of indicators impacting productivity that can be designated
under the socio-economic conditions present in both developing and developed
countries (Hasan et al., 2018). These indicators have been categorised into quantitative
and qualitative indicators; quantitative indicators are those that are physically
measurable and applicable by means of numbers, amounts and units, such as a report of
costs, completion percentage, the amount of materials and the number of human
resources, while qualitative performance indicators are those that are not easily and
tangibly measurable for example, the status of safety (Cox et al., 2003) or the
functionality of management (Botje et al., 2016). These indicators do not offer accurate
data on a project’s status, but describe a situation, such as a safety report (Cox et al.,
2003). The conceptual framework below (Figure 5.1) summarises the papers showing
the categories and subcategories of productivity indicators in construction projects
(Allmon et al., 2000; Arditi and Mochtar, 2000; Bassioni et al., 2004; Chan et al., 2004;
Chan and Kumaraswamy, 1995; Chan, 2009; Cox et al., 2003; Diamantopoulos and
Winklhofer, 2001; Dozzi and AbouRizk, 1993; Enshassi et al., 2013; Kapelko et al.,
2015; Meng, 2012; Poirier et al., 2015; Takim and Akintoye, 2002).
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Figure 5.1. Conceptual framework of key productivity indicators leveraging product success.
H1.Scheduling and planning
H2.Accounting
H3.Design and application of
software
H5.Estimating and costing
H6.Risks analysis
H7.Internet and electronic mail
(Site communication)
H8. Technical communication
H9.Guidline improvement
D1. Site management
D2.Office management
D3.Coordination mode of company
D4.Planning
D5.Scheduling
D6.Resource allocation
D7.Coordination with subcontractors
D8.Estimating
D9.Cost control
D10.Coordination among all stockholders
D11.Safety management
D12.Quality management
D13.Coordination with local authorities
D14.Marketing
D15.Coordination with research organizations
D16. Environment Management
D17. Sequence management
F1.Capacity
F2.Suitability
F3.Skilled
Operator
F4.Safety
F5.Replacement
F6.Maintainability
F7.Cost Control
A. Company Characteristic
B. Labor
C. Material
D. Management
E. Regulation
F. Machinery
G. Contract Condition
H. Information Technology
I. Engineering
K. External Circumstance
G1.Payment arrangement
G2.Incentive/.Disincentive clauses
G3.Risk Distribution among Parties
G4.Selection of:
• General Contractor
• Subcontractors
G5.Insurance
G6.Methods of dispute resolution
G7. Structure of Project’s
organization
Key
Productivity.
Indicators in
Construction
Projects
I1.Specifications
I2.Outcome& value
assessment
I3.Design standard
I4. Process& Procedures
A1. Financial strength
A2. Previous experience
A3. Company policy
A4. Human recourses
A5. Company assets
A6. Company size
A7. Management style
K1.Goal setting/ social
Justification (Social comfort)
K2.Time Study
K3.Quality Circles
C1. Delivery on time
C2. Availability of material.
C3. Material fees
C4. Procurement
C5. Availability of accessories
C6. Storage
C7. New products
C8. Prefabrication
B1. Incentive for crew
.arrangements
B2. Work conditions
B3. Loyalty
B4. Availability of labor
B5. Safety
B6. Quality control
B7. Working hours
B8. Workforce relation.
B9. Contract agreement.
B10. Local regulations
B11. Training
B12.Closure &Economic
difficulties
B13.Political/cultural situation
E1. Regulations of health.
E2. Regulations of environmental
E3. Local codes
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5.2.2 BIM and the level of adoption.
BIM is the process of developing and applying a simulated model of the
planning, designing, construction and operation of a building, which contains a
collection of data and rich information on all the details relating to a project during its
life cycle. BIM is a smart 3D CAD, automatically adaptable to any change and
connected to a database that acts as a common source for all parties involved in the
project.
BIM has moved into the areas of architecture, engineering and management. The
level of BIM uptake is determined by the activities for which it was designed to be used.
This determines the level of integration of practice and professionalism in a company
using BIM. Thus, the uptake level varies from one company to another (Haron et al.,
2010; Newton and Chileshe, 2012). Figure 5.2 presents the practices derived from BIM.
Chong et al. (2014) referred these practices to the common capabilities include
sequencing, clash detection, facility management, constructability assessment,
estimation and measurement (Chong et al., 2014). The improvement of conflict
management has been noted as a capability of BIM, as potential disputes can be better
controlled (Charehzehi et al., 2017).
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Figure 5.2. The potential practices of BIM in construction projects.
5.2.3 OSM and the level of adoption.
The OSM approach is a modern technique in which prefabricated construction
components are merged and erected as an on-site activity. The components are
produced off-site in a controlled manufacturing environment and then transported to and
positioned on the construction site (Blismas, 2007). The severe lack of construction
workers and material resources after the world wars of 1914–1918 and 1939–1945
opened the gate for the advent of OSM. Many terms have been considered for this
Drawings of as .built 3D
Modeling
Collaboration
Marketing
Site
co-ordination
TimeTracking spent
/Records
Scheduling
Tracking materials
Laser scanning
Walkthroughs
Virtual models of
reality.
Information generation
Assessment of design.
change
Digital plans for off-site
On-site BIM.-iPads, tablets.
etc
Material procurement
Management of site safety.
Waste.Management
BIM
practices/
capabilities
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concept (Vernikos et al., 2014), all of which, with a few variations in their applicability,
have resulted in the OSM system that is now commonly used (Amanda et al., 2017).
An industry report prepared by Sustainable Built Environment National
Research Centre (SBEnrc, 2017) declared the UK to be a pioneer in fostering and
benefiting from OSM, which had resulted in a noticeable improvement in their
construction programme, meaning that significant environmental, economic and social
benefits have been achieved via OSM. The market in the Asia-Pacific, as the most
demanding market for investment in OSM, has been calculated to amount to USD100
billion up until 2020. A report in 2012 showed that China had the largest market share
(60%), while the smallest market share belonged to Indonesia, at just 5%. Japan and
Australia shared 22% and 7% of this investment, respectively. It has been noted that the
rate of growth of the OSM market in Australia will dramatically increase due to the high
costs of both labour and importing manufactured components. Strengthening the
internal market and fostering job opportunities in Australia may thus be another main
reason for harnessing the OSM approach. Some obvious values arising from OSM are
‘reduced risk of delay, reduced likelihood of variation, increased construction safety,
more attraction to home buyers, greater return on equity, reduced material cost, less
theft, vandalism, and damage of material’ (SBEnrc, 2017, p.8-9). The costs of OSM-
based projects that are not applicable to non-OSM projects have been arguably assumed
to be a barrier to the uptake of the OSM approach (Blismas & Wakefield, 2009). Certain
extra costs have been seen to place pressure on projects due to the lack of systematic
uptake, highlighting which stage and how the uptake of OSM should be considered. The
uptake level may vary in between projects based on the characteristics and situation of
the project (Blismas & Wakefield, 2009). Although many researchers have identified
significant benefits from the utilisation of OSM, there are still barriers to embracing the
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OSM approach and reaping these benefits in Australia (Wynn et al., 2013). Every action
is crucial to support the decision regarding OSM uptake via offering supplementary
abilities to promote productivity and efficiency (Blismas & Wakefield, 2009).
5.2.4 The concept of interactions.
A combination of techniques may sometimes increase the capabilities of both
techniques. One proposed solution to the problem of cost overrun in the construction
industry is the concomitant application of lean and linear programming strategies as an
interacting measure (Gade, 2016). BIM, as an interactive technique, has been used to
influence the industry by providing a collaborative approach and an information-sharing
platform. For instance, the concepts of lean principles interact with BIM in both positive
and negative ways (Sacks et al., 2010). An enriched BIM model can effectively support
OSM projects at different uptake levels, subject to capturing suitable readable data
available in a BIM model and exchanging these with other stakeholders (Nawari, 2012).
Wynn et al. (2013) believe that construction efficiency can be promoted by an OSM-
oriented process that is supported by IT solutions such as BIM and Acconex.
5.2.4.1 BIM in OSM.
OSM, as an advanced technique, holds tremendous potential to interact with
BIM to contribute to improvements in the construction industry (Goulding et al., 2012).
Faster progress, quality and cost optimisation and minimisation of work corrections on
site; or in the broader sense, a more sustainable site, arise from the integration of off-site
produced units in a construction project (Arif et al., 2012; Khalfan and Maqsood, 2014).
Previous studies, however limited, have briefly discussed the potential benefits of BIM
in OSM. For example, BIM has been recognised as having the potential to link design,
manufacturing and construction through a workshop in relation to OSM (Goulding et
al., 2012). Vernikos et al. (2013, p. 152) interviewed 12 leading BIM experts and
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innovation directors and found that BIM can improve OSM through ‘configuration and
interface management; information data flow; project management and delivery;
procurement and contracts’. Nawari et al. (2012) stated that an enriched BIM model can
be effectively used by not only manufacturers to produce prefabricated components, but
also by users needing to capture all related data from the BIM model, which will
improve building processes in OSM-based projects. Ezacn et al., (2013) explained that
how BIM can cover some of the weaknesses of OSM that have been reported in the
literature. Amanda et al. (2017) revealed far greater benefits of BIM in OSM than in
traditional construction techniques by considering a range of parameters, such as time,
cost, quality, sustainability, market culture, poor integration and safety, among others.
The current research proposes an interaction between OSM and BIM through an
integrated framework for productivity improvement. As an example, precise
information on the details of a component, including its dimensions and assembly
descriptions, visible via BIM can assist fabricators to better position the component. to
exploit this capability, some researchers believe that design data are effectively
transferable into the prefabrication process in a factory environment via BIM’s capacity
to offer exact digital specifications, although others have stated that despite the BIM
specifications, the success of new concepts depends on organisational strategy
(Vernikos et al., 2014) and project governance functions (Hjelmbrekke et al., 2017).
5.3 Review Approach
The approach taken for the scoping review was to retrieve the necessary data
from the literature. This review approach consolidates the evidence on the research
variables on the basis of their potential links or synergies (Pham et al., 2014). This is
particularly useful for new topics and dealing with a lack of comprehensive literature
(Peters et al., 2015). Figure 5.3 shows the overall processes, along with the main
93
contents, that shaped the scoping approach. Through the literature review, six categories
were identified for improving construction productivity either individually or
synergistically: resources, management, engineering, procurement and contracts,
information technology and sustainability. The second stage involved searching the
channels of evidence, including the collection and filtration of the type of literature.
Relevant papers were identified by keyword searches of Google Scholar and library
databases, and their relevance was assessed by examining their abstracts was. The
keywords used in the searches were construction productivity growth/Improvement,
BIM capabilities, OSM capabilities, BIM in construction, OSM in construction and
BIM–OSM contribution. Figure 5.3 shows the selection process. In detail, the first step
of the selection process retrieved articles relating to performance and productivity in
construction. Thirty-four papers were identified, and following assessment, 27 were
retained based on the required productivity indicators. Next, these papers were scanned
to identify a clear understanding of the definition of BIM and OSM and their
capabilities. Twenty OSM-related papers and 57 BIM-related papers were screened,
with 16 and 50 retained, respectively. The identification process was followed by an in-
depth search on the current state of BIM–OSM interactions, from which seven relevant
papers were retrieved and analysed. The screening process was necessary to obtain and
analyse reliable and accurate sources of materials for the literature review. The research
questions were then developed, asking how BIM, OSM and BIM–OSM overlaps and
interactions may improve KPrIs. Finally, 100 journal articles covering the scope of
these techniques were selected.
94
Step 1: Scope clarification
Aim: To prepare a comprehension of the current state of BIM-OSM overlaps for
improved KPIs
Key Concepts for Investigation
No Categories BIM-related
Publications
OSM-related
Publications
BIM-OSM
related
Publications
Construction
Productivity/Performance
publication
1 Resources Did the papers
address KPrIs
improvements?
Did the papers
address KPrIs
improvements?
Did the papers
address KPrIs
improvements?
Did the papers address
KPrIs in construction? 2 Management
3 Engineering
4 Procurement
and contract
5 Information
Technology
Step 2: Searching channels for the evidence
Stages Resources Key words
Collection
Filtration
Google scholar search
Article journals
database search
Construction productivity growth/Improvement
BIM capabilities
OSM capabilities
BIM-OSM contribution
BIM in construction
OSM in construction
Step 3: Findings evaluation
Step 4: Combination and overlaps/ interactions
of the capabilities
Step 5: Conclusion
Figure 5.3. The selection process for the literature review.
95
5.4 Data Analysis and Findings
Table 5.1a shows the four research categories investigated in detail; namely,
construction productivity/performance, BIM in construction, OSM in construction and
BIM–OSM interaction. Productivity/performance growth and the indicators used in
construction projects were discussed from the first category of papers identified. The
role of BIM and OSM and their capabilities as standalone improvement approaches
were described from the second and the third categories, while the interactions between
BIM and OSM were investigated in the last category of papers. Table 5.1b summarises
the number of articles reviewed in each of the research areas.
Table 5.1a Peer-reviewed publications in the proposed research areas
No Academic researches Construction
performance/
Productivity
publications
BIM in
construction
publications
OSM in
construction
publications
BIM–OSM
Interaction
confirming
publications
1 Amanda et al. (2017) X
2 Ahmad and
Thanheem (2018)
X
3 Aliakbarlou (2018)
4 Allmon et al. (2000) X
5 Arashpour et al.
(2015)
X
6 Arditi and Mochtar
(2000)
X
7 Arif et al. (2012) X
8 Azhar (2011) X
9 Azhar (2012) X
10 Azhar (2009) X
11 Bank et al. (2010) X
12 Barati et al. (2013) X
13 Barlish and Sullivan
(2012)
X
14 Bassioni et al. (2004) X
15 Bi and Jia (2016) X
16 Blayse (2004) X
96
No Academic researches Construction
performance/
Productivity
publications
BIM in
construction
publications
OSM in
construction
publications
BIM–OSM
Interaction
confirming
publications
17 Blismas (2007) X
18 Blismas et al. (2006) X
19 Blismas and
Wakefield (2009)
X
20 Blismas et al. (2005) X
21 Bryde et al. (2013) X
22 Boyd (2012) X
23 Chan et al. (2004) X
24 Chan and
Kumaraswamy (1995)
X
25 Chan (2009) X
26 Charehzehi et al.
(2017)
X
27 Cheng and Lu (2015) X
28 Chen and Lu(2014) X
29 Chong et al. (2017) X
30 Chong et al. (2014) X
31 Chong et al. (2016)
32 Cirbini et al. (2015) X
33 Cox et al. (2003) X
34 Diamantopoulos and
Winklhofer (2001)
X
35 Ding et al. (2014) X
36 Ding et al. (2015) X
37 Dozzi (1993) X
38 Eastman and Sacks
(2008)
X
39 Murry (2003) X
40 Elnaas and Philip
(2014)
X
41 Enshassi et al. (2013) X
42 Ezcan et al. (2013) X
43 Ferrada and Serpell
(2013)
X
44 Forgues et al. (2012) X
45 Gade (2016) X
46 Ganah and John
(2014)
X
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No Academic researches Construction
performance/
Productivity
publications
BIM in
construction
publications
OSM in
construction
publications
BIM–OSM
Interaction
confirming
publications
47 Ghazali, W., &
Irsyad, W. A. (2016)
X
48 Goulding et al. (2012) X
49 Goulding et al. (2015) X
50 Hamidi (2012)
51 Haron et al. (2010) X
52 Hasan et al. (2018) X
53 Hergunsell et al.
(2011)
X
54 Haung (2009) X
55 Hjelmbrekke et al.
(2017)
56 Irizarry et al. (2013) X
57 Kang et al. (2007) X
58 Kapelko et al. (2015) X
59 Khalfan and Maqsood
(2014)
X
60 Khoshnava et al.
(2012)
61 Khosrowshani and
Arayici (2012)
X
62 Lee et al. (2015) X
63 Lessing et al. (2005)
64 Li et al. (2014) X
65 Love et al. (2011) X
66 Lu and Korman
(2010)
X
67 Lu et al. (2017) X
68 Meiling et al. (2012) X
69 Meng (2012) X
70 Moghadam (2012) X
71 Nawari (2012) X
72 Newton and Chileshe
(2012)
X
73 Olofsson et al. (2007) X
74 Pan (2012) X
75 Park et al. (2017) X
76 Pasquire et al. (2002) X
77 Pellinen (2016) X
98
No Academic researches Construction
performance/
Productivity
publications
BIM in
construction
publications
OSM in
construction
publications
BIM–OSM
Interaction
confirming
publications
78 Poririer et al. (2015) X
79 Popov et al. (2010) X
80 Porwal and Hewage
(203)
X
81 Sacks et al. (2010) X
82 Sacks et al. (2009) X
83 SBEnrc (2017) X
84 Shin et al. (2016) X
85 Segerstedt and
Olofsson (2010)
X
86 Smith (2014) X
87 Succar et al. (2009) X
88 Sulankivi et al. (2010) X
89 Takim and Akintoye
(2002)
X
90 Trani et al. (2015) X
91 Vernikos et al. (2014) X
92 Walker (2018) X
93 Wang et al. (2015) X
94 Wang and Love
(2012)
X
95 Wang and Chong
(2016)
96 Wong and Fan (2013) X
97 Wong and Fan (2014) X
98 Wynn et al. (2013) X
99 Zhang et al. (2010) X
100 Zhang et al. (2013) X
99
Table 5.1b Summary of the papers on BIM, OSM and performance
Research categories Number of the papers
BIM specification and capabilities in construction 50
OSM specifications and capabilities in construction 16
BIM–OSM interactions confirming papers 7
Construction performance/productivity 27
Total papers 100
5.4.1 The standalone OSM capabilities/functions for KPrIs.
Table 5.2 summarises the indicators that can be improved using standalone
OSM techniques, and reflects the relevant KPrIs in Figure 5.1. The following sections
discuss the ways in which the nominated KPrIs can be improved under OSM
functionalities.
Table 5.2 Nominated KPrIs affected by OSM functions
The nominated KPrIs
variables from Figure
4.1
The KPrIs’
signifier
Number of sources
of evidence
contributing to
effect on the
variables
Sources contributing to the
justification of interactions
Planning and
scheduling
D4&D5 3 Elnaas et al. (2014); Lessing et
al. (2005); SBEnrc (2017)
Safety D11 2 Blismas et al. (2005); SBEnrc
(2017)
Marketing D14 2 Pan et al. (2012); SBEnrc (2017)
Cost control D9 2 Pasquire& Connolly (2002);
SBEnrc (2017)
Site management D1 2 Arashpour et al. (2015); Meiling
et al. (2012)
100
Sustainability D9/D16/K1 3 Abanda et al. (2017); SBEnrc
(2017); Boyd et al. (2012)
5.4.1.1 Planning and scheduling.
Low-quality construction may result in rework or modifications. As
manufactured components are simply attachable in construction sites, rapid erection will
shorten the construction process (SBEnrc, 2017). Also, quality control may be more
feasible and precise in a controlled environment, due to better accessibility to the tools
required for quality measurement to comply with specifications (Elnaas et al., 2014).
Thus, the chances of any rework or correction being required on the site can be
minimised. In addition, the construction process can be simplified if it follows a
smoother plan and schedule, which leads to quicker completion. Off-Site Manufacturing
has rectified many problems in the construction industry, as well as improving planning,
scheduling and control, both off-site and on-site activities. These optimisations are
beneficial and productive in OSM-based construction projects (Lessing et al., 2005)
compared with non-OSM-based projects. Therefore, planning and scheduling of
services, such as supply, transportation and human resources management are able to be
improved in OSM-based projects.
5.4.1.2 Safety.
Occupational health and safety regulations are more easily observed in a
controlled working environment, such as a factory (Blismas et al., 2005). Injuries
arising from falls and collisions are more avoidable in these conditions, as the necessary
safety considerations are easier to meet (SBEnrc, 2017). Also, it is logical that the
reduced on-site activities required in an OSM-based project will result in fewer
construction crew members being required on the site, thereby reducing the likelihood
of injuries.
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5.4.1.3 Marketing.
Marketing is improved by attracting more clients/stakeholders. To be more
specific, promising a quicker construction period, along with high-quality products, is
attractive to homebuyers, who assume that earlier construction completion and
settlement in their homes will help them pay less rent and save more. This is also
attractive to investors, in that they will expect to achieve a quicker return on their
equity, while more rapid completion results in a project being sold more quickly.
Consequently, more rapid cash flow and capital return and re-investment will occur,
which is especially important for commercial projects (SBEnrc, 2017; Pan et al. 2012).
5.4.1.4 Cost control.
The 24-hour availability of materials in the site store prevents delays due to the
ordering process. The longer the completion, the greater the overhead costs. Conversely,
not only will the costs of multiple orders be eliminated, but also the purchase of a large
volume of materials at lower prices is possible. The cost of waste management is
another issue that is avoidable once waste and reuse-related issues are handled by the
factories. For example, no dumping costs are imposed (SBEnrc, 2017). In a controlled
environment, the chance of material protection is maximised, resulting in an economical
material cost due to material storage optimisation (Pasquire and Connolly, 2002). In
other words, any possibility of material damage arising from weather conditions and the
probability of vandalism, theft and mistakes as a result of human handling are
minimised.
5.4.1.5 Site management.
Reducing on-site construction activity and reducing congestion in these
activities also reduces human errors, resulting in better and more efficient site
management (Arashpour et al., 2015; Meiling et al., 2012).
102
5.4.1.6 Sustainability.
More controllable production reduces the chance of material wastage. This
contributes to environmental sustainability (less waste) and economic sustainability
(reduced costs due to less material usage). Energy consumption is also more efficient
due to more controllable on-site equipment and energy savings resulting from less trade
and activity disruption (Abanda et al., 2017). Safety considerations are promoted in a
factory environment. Further, workers can be provided with a comfortable environment,
as they do not work in severe weather conditions. This is associated with social
sustainability (SBEnrc, 2017). Each of these sustainability factors comply with the
‘people’ principles of OSM (Boyd et al., 2012).
5.4.2 The standalone BIM capabilities/functions for KPrIs
This section presents the KPrIs that contribute to improving a project via
standalone BIM functionalities. Table 5.3 presents the nominated KPrIs, as shown in
Figure 4.1.
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Table 5.3 Nominated KPrIs affected by BIM functions
The nominated KPrIs
from Fig 4. 1
The KPrIs’
signifier
Number of
sources of
evidence
contributing to
effect on the
variables
Sources contributing to the
justification of interactions
Sequence /Process
management
D17 2 Chen & Luo (2014); Wang & Love
(2012)
Site allocation &
accessibility
D1 2 Hergunsel (2011); Vernikos et al.
(2014)
Planning& Scheduling D4&D5 5 Barati et al. (2013); L. Ding et al.
(2014);
Kang et al. (2007); Hergunsel
(2011); Li et al. (2014)
Safety D11 3 Chen & Luo ( 2014); Khoshnava et
al. (2012); Ghazali& Irsyad (2016);
Sulankivi et al. (2010)
Social Sustainability K1 3 Ciribini et al. (2015); Wong & Fan
(2013); Eastman & Sacks (2008)
Economic
Sustainability
D9, C3& F7 3 Wong & Fan (2013); Azhar et al.
(2009); Ahmad and Thaheem (2018)
Environment
Sustainability
D16 2 Wong & Fan (2013);Lu et al. (2017)
Interface management D10&D7 2 Smith (2014); Olofsson et al. (2007)
Procurement& contract G7 1 Sacks et al. ( 2010)
Information data H3,5,8,9&D10 2 Hamdi & Leite (2012); Succar
(2009)
Value engineering I2 2 Park et al. (2017); Shin et al.(2016)
Concurrent engineering I4 2 Pellinen (2016); Succar (2009)
5.4.2.1 Sequence/process management
Under the BIM approach, information-sharing between stakeholders links all the
parties involved in a project, including the designer and the contractor, in a virtual 3D
model with BIM management tools revealing all the related details. All parties are able
to communicate easily to clarify any ambiguities or confusion (Chen & Luo, 2014;
Wang & Love, 2012).
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5.4.2.2 Site allocation and accessibility
The virtual site space created by BIM gives a good understanding of the ‘site
logistic plan’ (Hergunsel, 2011). This is enables the effective organisation of the use of
every location on the site in terms of the optimum layout of temporary offices, material
stock, siting equipment and plant, among others (Vernikos et al., 2014).
5.4.2.3 Planning and scheduling
Effective identification of potential problems affecting project planning and
scheduling is possible via a 3D BIM model, as all parties involved in a project are
linked through working on the same model at the same time and exchanging relevant
information (Barati et al,. 2013; Ding et al., 2014; Kang et al,. 2007). The application of
the critical path method and line of balance improve scheduling in BIM (Hergunsel,
2011).Through BIM, optimum resource management, which plays a significant role in
cost control, is achievable. Therefore, scheduling can be improved via BIM (Li et al.,
2014). This can be observed in both general planning/scheduling and re-planning/re-
scheduling.
5.4.2.4 Safety
When site activities are better organised there are fewer the incidents resulting
from site disruption. Through the virtual site environment model offered by BIM, safety
considerations are more observable through a ‘dynamic safety analysis’ (Chen & Luo,
2014); in particular, modelling of crane operation via BIM for site accessibility
(Khoshnava et al., 2012), for materials transfers, plant operations and equipment
movement, all of which will improve safety management. A 4D-BIM model provides
an optimum site layout and more effective safety plans (Sulankivi et al., 2010), which
can be ‘a starting point for safety planning and communication’ (Azhar et al., 2012,
p.83).
105
5.4.2.5 Social sustainability
The 3D model offered in the BIM system enables designers to invite clients to
review and impose any probable changes to a project to satisfy their needs and bidding
offers. Feedback from clients is received before the commencement of construction,
which not only prevents delay but also saves money, because any changes requested
after construction begins may be costly (Ciribini et al., 2015). The increased safety
offered via BIM can be considered social sustainability, as workers are in a safer
environment. This can also be considered a social factors in workers’ lives (Wong &
Fan, 2013), in that social sustainability focuses on people’s convenience (Eastman &
Sacks, 2008).
5.4.2.6 Economic sustainability
Through the virtual model offered by BIM, design and construction management
can be streamlined and improved (Wong & Fan, 2013). To achieve this, the best
decisions must be made for a project. For example, accurate information about the
materials required minimises budget waste arising from the purchase of superfluous
materials. The possibility of safety alerts also minimises the chances of compensation
payouts being necessary due to falls and collisions. Azhar et al. (2009) stated that BIM
returns 634–1633% of the initial investment. This confirms the satisfaction of economic
sustainability considerations. Ahmad and Thaheem (2018) also highlighted the
economic sustainability achieved in building energy consumption when BIM was
implemented.
5.4.2.7 Environment sustainability
Materials are not wasted once there is no requirement for construction
correction. More organised sites result in more efficient and effective activities, saving
material and energy (Wong & Fan, 2013). In fact, the optimisation of energy and
106
material consumption achieved via BIM implementation can protect the natural
environment and reflects both economic and environmental sustainability (Lu et al.,
2017).
5.4.2.8 Interface management
The ability to exchange readable data, subject to a compatible format, between
the parties involved promotes a professional interface and effective linking between
stakeholders (Smith, 2014). An informative link between the plumbing, electrical and
mechanical systems is a constructive collaboration on construction sites. The conflicting
activities of different teams sometimes affect each team, leading to the need for rework.
This problem is rectifiable by BIM (Olofsson et al., 2007), which offers interface
management possibilities.
5.4.2.9 Procurement and contracts
Lack of a procurement system and contracts suitable for BIM implementation is
a barrier to achieving the full benefits from the adoption of BIM, which offers reforms
on both the procurement and contract sides. The nature of information-sharing in the
BIM environment specifies every action required by all parties involved in a project
(Sacks et al., 2010). The definition of any likely required provision can be clearly given
in the contract once the commitments of each party are specified. The party responsible
for any defects or required actions is observable if the activities are monitored and
traced via the BIM environment, which prevents disputes and contract complexity.
5.4.2.10 Information data flow through virtual model quality and data
richness
In addition to a quality virtual model generating accurate information, a rapid
line of communication for the exchange of data are provided by the BIM model (Hamdi
et al., 2009). This removes any doubts regarding the requested specification of materials
107
and elements and their integrity. Moreover, this function is also able to bridge the divide
between academia and industry to allow further improvement of BIM guidelines as it is
being practised.
5.4.2.11 Value engineering
A BIM-based value engineering (VE) idea bank enables stakeholders achieve
rapid data retrieval from past experience at the idea generation phase (Park et al., 2017).
Further, the nature of this information-sharing platform links the stakeholders to each
other to assess the consequences of a design or apply alternatives. In other words, an
assessment of the feasibility of every change in terms of technical and cost factors is
possible immediately via this smart virtual model, as the other parts of the model
automatically update themselves with the changes. Under the VE process, the virtual
model can return to the baseline by an undo function, with no money, energy or time
being spent in reality. This confirms the sustainability aspects of a BIM-based VE (Shin
et al., 2016).
5.4.2.12 Concurrent engineering
The theme of concurrent engineering can be clearly seen in BIM if there are the
opportunities to fast-track activities or carry them out in parallel (Pellinen, 2016;
Succar, 2009). As an example, the process of reviewing and confirming the designs, in
terms of executive technical requirements, can be shortened by combining the models
virtually (reviewing processes at the same time) rather than handing over the models
sequentially and undertaking a paper-based model evaluation.
5.4.3 The interaction of BIM and OSM for KPrIs
Table 5.4 presents the potential OSM–BIM interactions. It justifies how these
interactions occur and improve KPrIs once both techniques are applied simultaneously.
The KPrIs to be improved are listed in the left column. The next column presents the
108
relevant KPrIs from Figure 5.1, while the third column presents the sub-sections
explaining OSM–BIM interactions. Lastly, the fourth column reveals the sources
contributing to the justification of the OSM–BIM interactions.
Table 5.4 A summary addressing the improvements achieved via OSM–BIM interactions
The nominated KPrIs for
improvement from Figure
4.1
The KPrIs’
signifier
The interactions
descriptions No
via OSM–BIM
implementation
Sources contributing to the
justification of interactions
Sequence /Process
management
D17 Interaction 4.3.1 Lu and Korman (2010); Irizarry
(2013)
Site allocation &
accessibility
D1 Interaction 4.3.2 Vernikos et al. (2014); Trani et al.
(2015)
Planning& Scheduling D4&D5 Interaction 4.3.3 Bank et al. (2010)
Safety D11 Interaction 4.4.4 Zhang et al. (2013); Irizarry et al.
(2013);
Zhang et al. (2010)
Social Sustainability K1 Interaction 4.4.5 Wong & Fan (2013)
Economic Sustainability D9, C3& F7 Interaction 4.4.6 Wang& Chong (2016)
Environment Sustainability D16 Interaction 4.4.7 Wang& Chong (2016);
Wong & Kuan (2014)
Interface management D10&D7 Interaction 4.4.8 Smith (2014)
Procurement& contract
G7 Interaction 4.4.9 Barlish & Sullivan (2012)
Information flow via virtual
model quality& data
Richness
H3,5,8,9&D10 Interaction
4.4.10
Haron et al. (2010); Ezcan et al
(2013); Lee et al. (2015); Popov et
al. (2010); Sacks et al. (2010)
Value engineering I2 Interaction
4.4.11
Forgues et al. (2012)
Concurrent engineering I4 Interaction
4.4.12
Goulding et al. (2015)
The following sections discuss how these two techniques may interact
constructively throughout a project.
5.4.3.1 Sequence/process management
The information-sharing capability in BIM will remove the issue of
fragmentation between the different parties involved in a project (Lu and Korman,
2010). The sequences of OSM-based projects include design, order, component
109
production, transfer and the installation process. As has been explained, BIM is capable
of improving construction supply chain management through an integration process.
The effective monitoring of resources is possible by linking and visually representing
the process (Irizarry, 2013). As Irizarry (2013, p.241) claimed, providing the digital
geographic information of a construction site enables experts to sequentially keep track
of the ‘flow of materials, availability of resources, and map of the respective supply
chains’. The manufactured components can also be deemed as the material in OSM-
based projects. This optimises the identification of manufactured components at the
stocking and dispatching stages.
5.4.3.2 Site allocation and accessibility
The virtual visualisation of objects provides the contractor a rapid and improved
visual evaluation when comparing the planned and actual specifications and allows
easier identification of any failure in the arrival of components. Thus, the placement of
faulty and sound components is organised efficiently upon their arrival (Vernikos et al.,
2014). Organising and assigning space to every group of components via a virtual space
is more practical for organising the site in terms of accessibility to both the components
and the relevant area of the site (Trani et al., 2015).
5.4.3.3 Planning and scheduling
The manufacturer, as a part of the project team, is linked to the other parties, not
only in the main planning and scheduling of the project, but also in the case of any rapid
changes. A collaborative environment and information-sharing platform for ‘early
decision-making’ (Bank et al., 2010) is the main capability of BIM, playing a dominant
role in both the main planning/scheduling phase, and any correction planning/re-
scheduling.
110
5.4.3.4 Safety
Under effective management of the activities in a BIM–OSM project, all
activities are optimally organised and formulated, thereby reducing complexity, which
results in fewer accidents. Modelling of the assembly of the prefabricated components
in BIM enables contractors to review the erection and positioning process virtually,
which may reveal any potential unobserved safety shortcomings (Irizarry et al., 2013).
The likelihood of falls (Zhang et al., 2013) and collisions due to plants operations in
OSM-based projects is high due to the dispatch and movement of components dispatch
on the site. BIM is able to reveal the probable fall situations from heights, identify the
best access routes for plant operations, and offer lifting drawings for crane activities,
which will minimise the chances of reportable incidents (Zhang et al., 2010).
5.4.3.5 Social sustainability
BIM enables a constructive interaction between designers, manufacturers and
contractors by offering accurate information in terms of the units’ quality specifications
and properties, which can be deemed as comfort in the professional life (Wong & Fan,
2013). This reflects an easing in professional life, equivalent to social sustainability.
5.4.3.6 Economic sustainability
Flexibility in an OSM-based project is highly limited once the units are
transferred to the construction site. Through the capability of clash detection and
accurate data via BIM in an OSM-based project, the chance of any extra activities
required for rework is limited. Since any rework comes with excessive use of
workforce, equipment, plant and material removal and reuse, minimising the chance of
rework satisfies the aspects of material waste as well as work hours (Wang and Chong,
2016).
111
5.4.3.7 Environmental sustainability
Material usage is more efficient and accurate in a controlled environment. On
the basis of an exact quantity of material determined via BIM, both the chance of
material waste and rework are minimised, satisfying environment sustainability
requirements (Wang & Chong, 2016). The construction site is more organised once the
job shifts from the factory to the construction site. In fact, the workspace is more
efficient due to the reduced number of activities required and the smaller workforce
compared with a more congested traditional construction site. The need for fewer trades
working at the same time results in less noise and less emissions from equipment.
Reduced on-site activity also means more efficient energy consumption. Thus, it can be
claimed that BIM is effective from the point of view of environmental sustainability
(Wong & Kuan, 2014).
5.4.3.8 Interface management
BIM provides a constant communication line with the other parties, including
designers, construction contractors (Smith, 2014) and manufacturers that is accessible
with no waiting time. Therefore, information and data are exchangeable with
manufacturers, as parties involved in a project, in the form of readable formats
consistent with BIM.
5.4.3.9 Procurement and contracts
A BIM-based contract in an OSM-oriented project carries significant
responsibility for the parties involved in meeting the project requirements, from data
production to executive operations, as fragmentation between the design and delivery
teams can be controlled at an early stage. No time is wasted on disputes to identify the
party responsible in case of errors or failures, as the organisational structure is clear.
Also, in the case of any changes, the manufacturer can be notified more rapidly due to
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the BIM information-sharing platform, and the production line can be immediately
modified to take the steps required for the change because under a BIM model, the
management of the drawing process and any technical review is more rapid than with
other techniques (Barlish & Sullivan, 2012). Thus, the determination of responsibility
for faulty components can be managed within the contract.
5.4.3.10 Information data flow through virtual model quality and data
richness
The capacity of BIM to provide transparent and accurate specifications, as well
as to share data, enables the manufacturer to participate in the assembly guideline
definition, indicating the exact procedures to position manufactured components. This
capability originates from ‘model quality and data richness’ (Haron et al., 2010). It
enables the manufacturer to efficiently recognise all the parts of a component for the
purpose of assembly (Ezcan et al., 2013), which is important for contractors on the
construction site. This confers simple accessibility and easy observation of data and thus
an effective data flow (Lee, Eastman, & Lee, 2015) between the designers, the
contractors and the manufacturers. In addition, under BIM the ability to identify
repetition enables designers and manufacturers to recognise more automation
opportunities for ‘series production’, resulting in cost saving due to ‘virtual object-
oriented design’ (Popov et al., 2010; Sacks et al., 2010).
5.4.3.11 VE
The effect of changes to manufactured components (constructability) can be
assessed under a BIM model, which also allows cost evaluations (Forgues et al., 2012)
prior to any actions in the real project (feasibility via VE). It can be claimed that VE is
much more effective for VE than merely brainstorming via paperwork. Therefore, VE is
achievable in a BIM–OSM-based project.
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5.4.3.12 Concurrent engineering
Concurrent engineering has been introduced to the industry as one of the
techniques able to reduce project process time through fast-tracking activities or running
activities in parallel (Goulding et al., 2015). For example, the components may be
produced while site preparation is in progress. Concurrent engineering is achievable
within OSM–BIM projects on the assumption that any incompatibility of components
would disturb the fast-tracking plan (running activities in parallel) in OSM-based
projects. By providing the exact specifications for all components and continuous
information-sharing and communication between the designer, contractor and
manufacturer, the chances of on-site rework efforts to rectify or adjust components, as
well as the chance of rejection of components, is minimised. Thus, the fast-tracking
plan for concurrent engineering is not hindered in OSM–BIM projects.
5.5 Integrated Framework
This research has highlighted the interactions between OSM and BIM and their
contribution to construction performance in a broader sense, as well as to construction
productivity in a narrow sense. It has justified each capability of OSM and BIM
independently, as well as the capabilities of the concurrent application of OSM–BIM
(OSM–BIM interactions), respectively. Figure 5.4 illustrates the integrated framework
that leads to improved overall project performance. It consists of three stages: input,
process and output. At the input stage, the data are derived from the capabilities of BIM
and OSM that have the potential to interact with each other. It shows that the concurrent
application of the capabilities that have the potential for OSM–BIM interactions
(POBIs) can result in improved KPrIs, subject to their systematic adoption. Systematic
adoption refers to the proper and concurrent practice of the techniques’ capabilities at
both the design and the construction stages. The improvement measures result in overall
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project performance. It is expected that construction professionals can improve project
productivity by considering the 12 KPrIs through the interactions of BIM and OSM (as
shown in process stage). The KPrIs may be addressed by interactions through the
optimisation of the work breakdown structure at the design and construction stages.
Subsequently, the technical specifications and contractual requirements can be
formulated before the construction stage so that these interactions can be applied.
Low productivity has always been one of the main challenges for the
stakeholders in the construction industry, particularly from the continuous improvement
perspective. The proposed integrated framework provides useful references to the
potential productivity areas that need to be targeted in a project, and which may help to
achieve the highest level of project productivity and performance. It also promotes the
effective adoption of BIM and OSM in the future.
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Figure 5.4. Integrated framework of OSM–BIM interactions for productivity improvement.
Improved KPrIs
via OSM–BIM
interaction
BIM capabilities
1. Information generation/sharing
platform
2. Constructability assessment
3. Measurement/ Estimation
4. Clash detection
5. Facility management
6. Sequence clarification
7. Safety Management
OSM capabilities
1. Automation
2. Safety considerations
3. Sustainability considerations
4. Employment opportunities
5. Faster investment return
6. Series production
Input
Design
Construction
Overall project
performance
Social
sustainability
Concurrent
engineering
Safety
consideration
s
Procurement
& Contract
Site allocation&
accessibility Planning&
scheduling
Value
engineering
Interface
management
Economic
sustainability
Environment
sustainability Information
flow Sequence&
Process management
Process Output
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5.6 Discussion and Conclusion
This research project has critically reviewed the literature in order categorise
KPrIs for construction projects, and identified the indicators that can potentially be used
to improve productivity and performance via the capabilities of OSM and BIM, both
independently and together. It has addressed seven BIM-based capabilities and six
OSM-based capabilities individually, as well as 12 POBIs relevant for KPrIs
improvement from the productivity perspective. Figure 4.3 showed a scoping review
was used to identify these capabilities, and 100 journal articles were carefully analysed
under four main research categories: construction productivity/performance, BIM in
construction, OSM in construction and OSM–BIM interactions. This revealed the
capabilities of the OSM and BIM techniques, and 12 potential interactions to achieve
KPrIs improvement within ten categories: company characteristics, materials, labour,
management, regulation, machinery, contract condition, information technology,
engineering and external circumstances.
The main advances of this scoping review paper are: (a) the first systematic
discovery of the 12 potential interactions between OSM and BIM and their benefits in
productivity improvement; and (b) the integrated framework (Figure 4.4) that addresses
KPrIs improvement at the design and construction stages. The related previous studies
have only briefly discussed the integration of BIM and OSM at a preliminary stage of
the building processes (Nawari et al., 2012), the management drivers (Vernikos et al.,
2013), the required BIM functionalities (Ezcan et al., 2013), and the potential benefits
(Goulding et al., 2012; Amanda et al., 2017). The identification of these interactions
between BIM and OSM extends the existing body of knowledge, especially for the
effective implementation and management of OSM–BIM-based projects. The
productivity indicators identified as useful for improvement by OSM and BIM can
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serve as a guideline and benchmark for organisations, which they can use to streamline
their resources and operations to enable them to achieve the desired outcomes of their
projects. Moreover, the findings of this paper are generalizable to both developed and
developing countries.
However, certain limitations need to be considered, such as the exclusion of the
latest publications in the proposed four research categories, the lack of empirical
research in recognising the degree of impact and practicability of the OSM–BIM
interactions, and for the prioritisation of each key productivity indicator. Future research
could investigate the complex cause-effect relationships between BIM and OSM
capabilities and their interaction. As a part of a larger research project, this paper will be
followed by statistical analysis using Structural Equation Modelling (SEM) to reveal the
degree of practicability of these interactions. A range of hypothesised interactions will
be evaluated and judged by experienced practitioners. The results of these investigations
will be applicable to improving the planning and managerial stages for productivity
improvement in OSM-based projects. A case study would be complementary to the
current research to evaluate the practicability of the interactions and to uncover potential
barriers in the pathways of OSM–BIM-based projects.
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Chapter 6: Appraisal of Potential Interactions Between
Building Information Modelling and Off-Site Manufacturing
for Project Performance
Pejman Ghasemi Poor Sabet1; Heap-Yih Chong2;
Chamila Dilhan Dushantha Ramanyaka3
1School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia,
2School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia.
3School of Design and the Built Environment, Curtin University, Perth, WA 6102,
Australia.
E-mails: [email protected]; [email protected];
Abstract
The high demand for improvements in construction productivity has led to the emergence
of advanced techniques such as building information modelling (BIM) and off-site
manufacturing (OSM). Many studies have discussed the individual capabilities of BIM
and OSM, but limited studies have qualitatively and quantitatively explored the
concurrent application of these techniques. In this study, an in-depth evaluation was
conducted to determine the influences of OSM–BIM interactions on overall project
performance. Structural equation modelling method was adopted to examine the complex
relationships among research variables based on survey data. Survey respondents
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comprised construction practitioners across Australia. The results show that the
individual application of OSM or BIM had no significant influences on the overall project
performance, but a systematic adoption of the interactions as a mediator between OSM
and BIM, significantly enhanced the overall project performance as measured by key
productivity indicators. The technicalities of these interactions are applicable at the
planning and managerial stages, enabling efficient project functioning in hybrid OSM–
BIM-based projects. From the broader perspective, the research also contributes to the
diffusion of innovation in the construction industry.
Keywords: Systematic adoption, construction productivity, interactions.
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6.1 Introduction
The construction industry is a major contributor to the economy of countries
(Klufallah et al., 2018). Countries have upgraded construction methods, aiming to
respond to the demand for a sustainable level of construction productivity that
contributes to the economic growth (Hosseini et al. 2018). The observed decline in
construction productivity has challenged economy and resulted in the emergence of new
techniques (Dolage & Chan, 2013). The search for such techniques has prompted
management to consider ways of addressing factors that contribute to poor productivity.
Fragmentation among project stakeholders is at the root of poor productivity. Yahya
(2010) found that modern construction techniques could resolve malfunctioning systems
in construction projects. Many construction companies aim for an efficient flow of
accurate information among project stakeholders at both the pre-construction and
construction stages to improve quality (Zeng, Lou, & Tam, 2007) which is an aspect of
performance. The application of advanced techniques has been observed to improve the
efficient flow of information. Quick and efficient responses from stakeholders is a key
factor in project value creation. Improved control over activities is another means of
eliminating inefficiencies that may occur in dynamic environments such as construction
sites (Kenley, 2014). Building information modelling (BIM) and off-site manufacturing
(OSM) have been identified as two revolutionary techniques capable of addressing the
issues threatening construction productivity.
A hybrid team compromises planner, designer, contractor (Hosseini et al. 2018),
and manufacture as project stakeholders in a construction project. The quality of
communication among these project stakeholders plays an essential role in project
progress (Hosseini et al., 2016). BIM provides these parties with an accurate
information-sharing platform for reliable communication (Hosseini et al., 2017) and the
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ability to visualise project status, resulting in the efficient coordination between parties
involved in projects. The United States and United Kingdom (UK) have developed
regulations and standards on BIM adoption, supporting its applicability (Lea et al.,
2015). Indeed, the UK government has mandated that all public sector projects adopt a
minimum of level 2 BIM (Khosrowshahi & Arayici, 2012). OSM provides a more
controlled working environment and standardised building components. It was
developed to optimise resource utilisation, meet higher expectations of quality,
accelerate production lines and increase the effectiveness of safety measures, which
together contribute to higher productivity levels (Blismas, 2007). Applied individually,
these techniques have not been observed to cover all aspects of productivity; however,
when applied concurrently, the interactions between these two approaches have been
found to satisfy more areas of productivity.
Sabet and Chong (2018) clarified the boundaries between productivity and
performance, claiming that performance outcomes may be met by improving
productivity indicators. From this perspective, both techniques are justifiable for
improving productivity indicators and final project performance. However, efforts to
implement OSM and BIM have so far failed to fulfil their objectives because of the lack
of research advising on their systematic adoption. Technological evolution takes time,
and concrete evidence of the practical value of new techniques and innovations is
needed. Goulding et al. (2012) developed an enriched BIM model to fill the gaps in
OSM-based projects such as poor linkages between people, processes and technologies.
BIM links the design, manufacturing and construction stages, enabling all parties to
access relevant data (Nawari et al., 2012). These linkages have changed traditional
practices in the construction industry. Amanda (2017) highlighted the enormous
benefits of BIM–OSM-based projects compared with traditional construction projects.
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Yin et al. (2019) identified a range of research gaps in BIM for OSM. Therefore, the
supporting objectives to achieve the overall aim are: (a) to examine the influences of the
standalone capabilities of OSM and BIM on project performance via key productivity
indicators (KPrIs); and (b) to develop the interactions between OSM and BIM and
determine the influences of these interactions as a mediator between the two approaches
on overall project performance via the improvement of KPrIs. Structural equation
modelling (SEM) was the approach to analyse data. A questionnaire survey was used as
the data collection tool. Respondents were construction practitioners familiar with OSM
and BIM in Australia. This study aims to highlight the practicalities of the interactions
between the two approaches to encourage clients and practitioners to embrace OSM–
BIM-based projects. The study also provides insights on technical details at the
planning stage to improve the management of hybrid OSM–BIM-based projects.
The rest of this paper is structured as follows. Section 2 discusses the need for
improved construction productivity. BIM–OSM interactions are offered as possible
solutions. Section 3 focuses on the primary research model and development of
hypotheses. Section 4 presents the research approach and stages and the application of
SEM. Section 5 presents the data analysis and findings. Section 6 concludes the paper.
6.2 Literature Review
6.2.1 Construction productivity.
Productivity issues in the construction industry have been flagged for a long time.
Efforts toward industry innovation have not addressed the need to improve productivity
indicators (Barbosa et al., 2017). In addition to innovating in projects, it is crucial to
adopt a range of productivity fundamentals (Sabet & Chong, 2020). Sabet and Chong
(2020) argued that a lack of integrated management, competent workforce, modernised
equipment or strategies of adoptability, and an inappropriate or partial technique
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application may impede productivity trends. Productivity has many aspects—all of
which should be addressed for successful productivity outcomes. Sabet and Chong
(2018) categorised KPrIs into “company characteristics, materials, labour, management,
regulation, machinery, contract condition, information technology, engineering and
external circumstances” (p. 18). They discussed that an improvement in these indicators
results in better productivity and enhanced final project performance. The in-project
application of some techniques affects KPrIs directly, while others have an indirect
effect. However, productivity levels are not yet satisfactory because emerging
techniques can only cover some of these KPrIs (Sabet & Chong, 2019). This means that
productivity continues to lag behind demand. Javed et al., (2018) considered
productivity the ratio between resource input and construction output. Resistance to
change is at the root of unsuccessful efforts to improve construction productivity (Lines
et al., 2015). Ineffective changes are associated with potentially costly errors, so
practitioners and authorities consider change risky (Motawa et al., 2006), and are often
unwilling to implement new practices. Therefore, innovations have not been
systematically implemented or have only been partially practiced (Hall, Algiers, &
Levitt, 2018). Among the emerging approaches to productivity improvement, OSM and
BIM have attracted the attention of authorities as being capable of significantly
improving productivity and overall project performance. Hamdan et al. (2015) found
that the concurrent application of these two approaches offers a wide range of
capabilities that lie in more areas of productivity.
6.2.2 Project Performance
The desire for project performance to secure profitability for stakeholders, clients, and
end-users has resulted in upgraded construction methods. However, the ever-changing
nature of the construction industry challenges the adaptability of these techniques. It also
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challenges the practicality of a technique’s capabilities within a system (Ferrada &
Serpell, 2013). Further, this dynamic environment may disturb the progress of a project,
by challenging the line of communication between stakeholders and data flow (Holt,
2015). Therefore, inefficiencies in time, cost, safety, and quality may be unavoidable. The
consequent dissatisfaction among stakeholders gives rise to disputes within a project,
which further impede the expected level of project performance. Walker (2018) stated
that a collaborative environment is crucial for enhancing the performance level of a
project, while Jha and Iyer (2006) asserted that the factors of time, cost, quality, safety,
and stakeholders’ satisfaction compromise overall project performance. In the literature
surrounding project performance, “performance” and “productivity” are used
interchangeably (Dozzi& AbouRizk, 1993). In other words, these two schemes are
alignment with each other.
6.2.3 Background on OSM.
The modernisation of construction has seen the emergence of OSM in which
standardised construction components are produced, transported and assembled at
construction sites. A considerable attention to OSM have been paid to the market of
UK, Malaysia, Hong Kong, China and Australia (Li et al., 2014). Other terms for OSM
include industrialised building and prefabrication (Khalfan & Maqsood, 2014). Tam et
al. (2007) found that OSM significantly reduces not only waste but also cost and time
because fewer resources need to be allocated to waste management. Arif and Egbu
(2010) found that the use of preassembled components optimises quality, reduces the
need for resources, improves health and safety, increases the integration of project
stakeholders and reduces the cost of the final product. Volumetric and non-volumetric
preassembly are applicable at different stages of construction and include prepared
concrete, structural components, wall panels, mechanical and electrical parts, and even
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complete units (Li et al., 2014). Overall, a wide range of joinery parts, including
volumetric, non-volumetric components and building services, are available for
assembly in construction projects (Blismas & Wakefield, 2009). Many studies have
been carried out on OSM in the last decade, but there is still room to improve
operational, management and strategic considerations to make OSM more applicable in
the construction industry (Hossieni et al., 2018).
6.2.4 Background on BIM.
BIM is a very considerable innovation that has extensively appeared in the
architecture, engineering and construction industry (Issa & Olbina, 2015; Hossieni et
al., 2018). It refers to ‘a new approach to design, construction, and facility management
in which a digital representation of the building process is used to facilitate the
exchange and interoperability of information in digital format’ (Mutis et al., 2018, p.
137). Some governments have identified and recommend BIM as an effective strategy
to address construction productivity failure. As a pioneer of BIM, the UK has mandated
the application of level 2 BIM in government projects (Love et al., 2015). Irizarry et al.
(2012) point out that the major capabilities of BIM are the visualisation of construction
status and access to exchangeable information by project stakeholders. Hossieni et al.,
(2017, p. 1) discussed that BIM transformed facility management by providing
‘different forms of data and information’. The adoption of BIM has rapidly increased,
and different companies apply various levels of BIM with respect to expertise and client
demands (Jung & Lee, 2015). Due to the BIM’s influential capabilities, the role of BIM
and its application are worth undergoing further analyses from the perspective of
diffusion innovation theory (Hosseini et al., 2018).
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6.2.5 Interaction between OSM and BIM.
BIM offers rich, supportive information management abilities, enabling it to
facilitate other innovative techniques and building methods (Abanda, Tah, & Cheung,
2017; Ezcan et al., 2013). The systematic adoption of BIM with other approaches may
provide overlapping capabilities, maximising the functionality of both approaches. This
concept accelerates the maturity of BIM, resulting in the operational and strategic
extension of BIM implementation (Khosrowshahi & Arayici, 2012). For example, BIM
can be effectively paired with lean construction techniques to provide a collaborative
environment (Sacks et al., 2010). Wynn et al. (2013) found that the information
technology–based nature of BIM can enhance the efficiency of OSM. The lack of
empirical studies on the applicability of BIM in OSM means that the relationship
between these two approaches is unclear (Tang et al., 2019). Sabet and Chong (2019, p.
7) have highlighted the potential for collaboration between the two approaches,
resulting in ‘faster progress, quality, safety, cost optimisation, and minimisation of work
correction on site’ or, broadly, a more sustainable project from the concept to
construction stages. However, Jang and Lee (2018) argue that coordination between
mechanical and electrical systems at construction sites is a time-consuming process that
requires additional person-hours because of some required adjustments in the assembly
stage. Therefore, the coordination of activities plays a vital role in the successful
establishment of OSM–BIM systems. Ezcan et al. (2013, p. 7) have argued that
‘providing an improved design, facilitating collaboration and covering accurate and
extensive amounts of information’ seem to be the most useful benefits of BIM in OSM-
based projects’. Nawari (2012) claims that BIM standards and provisions specifically
designed for OSM can guarantee efficiency and productivity in OSM-based projects.
Vernikos et al. (2014) demonstrated that BIM is capable of improving OSM, but its
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application in OSM has been limited. The lack of evidence on the potential applicability
of BIM in OSM has been flagged as a reason for construction clients and practitioners
being unmotivated to apply the full capacity of BIM in OSM (Abanda et al., 2017;
Gibb, 2014). Liu, Chen and Al-Hussein (2019, p. 84) have identified ‘BIM-based
generative design for prefabrication’ as one of the areas requiring further research.
6.3 Research Model and Hypothesis Development
Given the lack of sufficient research studies quantifying the relationships
between BIM, OSM and KPrIs, a hypothetical model comprising four constructs was
developed for the present study (see Figure 6.1). As Figure 6.1 shows, the standalone
capabilities of the two approaches as well as their interactions play the role of
independent variables, while overall project performance (reflected by KPrIs as
discussed earlier) is the dependant variable in the research.
Figure 6.1. Hypothetical research model.
6.3.1 BIM and project performance.
BIM is an approach in which the integration of graphical and non-graphical
information enables project stakeholders to collaborate more efficiently throughout a
project’s life cycle (Pezeshki et al., 2019; Mutis & Hartmann, 2018; Vozzola et al.,
2009). Mutis et al. (2018, p. 137) stated that BIM is ‘a new approach to design,
H6
H5
BIM
capabilities
Interactions
between OSM
and BIM
OSM
capabilities
H1
H4
H2
H3 Overall project
performance
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construction, and facility management in which a digital representation of the building
process is used to facilitate the exchange and interoperability of information in digital
format’. From the existing literature, Ghaffarianhoseini et al. (2017) reflected on the
capabilities of BIM applicable at different stages, including model clarification, site
coordination, constructability assessment, measurement and estimation, model unifying
and clash detection, sequence clarification and information transfer and sharing. In
addition to these attributes, Sabet and Chong (2019) claim that the opportunity for
safety management provided by BIM can also improve productivity. Therefore, the
existing literature shows that there is merit in conducting an in-depth evaluation to
obtain a holistic understanding of how effectively the BIM capabilities align with the
aspects of project performance. A part of this paper makes the application of BIM more
visible from the productivity perspective. The following hypothesis was developed to
assess this claim:
H1: BIM has a significant influence on overall project performance.
6.3.2 OSM and project performance.
OSM is an approach in which prefabricated construction components are used at
construction sites (Khalfan & Maqsood, 2014). This approach benefits clients in terms
of faster and safer construction processes (Arif & Egbu, 2010) and higher sustainability
via the ‘3R concept (reduce, reuse, and recycle)’ (Hamid & Kamar, 2012, p. 7). OSM
enables clients and contractors to overcome challenges, including schedule disruptions,
adverse site conditions and a shortage of skilled labour. The Sustainable Built
Environment National Research Centre (2017) asserts that a controlled environment can
minimise the likelihood of negative effects arising from sub-optimal material usage and
scheduling, safety and quality issues. The minimisation of negative impacts that may
lead to rework in construction projects consequently enhances productivity (Hughes &
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Thorpe, 2014). OSM provides construction projects with better productivity in
comparison with traditional methods of construction (Eastman & Sacks, 2008). Based
on the existing relevant literature, Sabet and Chong (2018) have listed the key OSM
attributes as automation and series production, faster investment return, more
comfortable working conditions, sustainability and safer operations. OSM capabilities
and potential benefits have increased its demand, which has been predicted to increase
globally. To promote its domestic housing market, Australia should accelerate the
implementation of OSM (SBEnrc, 2017). However, criticisms of the applicability of
OSM have disrupted these trends (Wynn et al., 2013), and research on how to improve
its applicability to guarantee its benefits is warranted. Given that OSM appears capable
of enhancing productivity indicators, research that quantifies the efficiency of its
capabilities on project performance may enrich the understanding of the applicability of
OSM. To contribute to the adoption of OSM in the market, the following hypothesis
was developed:
H2: OSM has a significant influence on overall project performance.
6.3.3 OSM–BIM interactions and project performance.
Sabet and Chong (2019) reviewed related works on BIM in OSM (as discussed
in section 2.4) and identified 12 potential OSM–BIM interactions that are capable of
improving KPrIs, leading to optimal performance. They have called for an empirical
study to explore the practicality of these interactions. These potential interactions
pertain to site allocation and accessibility, planning and scheduling, safety,
sustainability, procurement and contracts, VE, interface management, information flow,
sequencing, location management and, last but not least, concurrent engineering. To
investigate the relationships between the two approaches that may positively influence
130
these factors and overall project performance, the following hypotheses were developed
to be tested via the SEM method:
H3: BIM has a significant influence on OSM.
H4: OSM has a significant influence on OSM–BIM interactions.
H5: BIM has a significant influence on OSM–BIM interactions.
H6: OSM–BIM interactions have a significant influence on overall project
performance.
6.4 Research Approach
Figure 6.2 depicts the stages of this research. The first stage involved a literature
review on BIM, OSM and BIM in OSM, followed by the identification of research gaps.
As discussed in section 3, six hypotheses were developed to evaluate the relationships
between latent and observable variables. Table 6.1 displays the constructs as well as the
observable variables by which the latent variables could be measured. Observable
variables were discussed with several experts and seniors who had a holistic
understanding of the two approaches. Their wealth of experience in academia and
industry enabled the researcher to identify observable variables, which were used to
develop a questionnaire as the data collection tool after ensuring that the capabilities
and interactions of OSM and BIM were properly represented. Further, the
comprehensibility of the observable variables was tested in a pilot study with ten
randomly selected construction practitioners prior to the survey being conducted. SEM
was applied for data analysis and consisted of reliability examination and hypothetical
tests. Finally, the hypothesis test results determined whether the hypothetical model was
confirmed or needed revision.
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Figure 6.2. Flowchart of research stages
Table 6.1 SEM measurements
Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
BIM 3D 3D modelling A detailed virtual
BIM offers spatial,
executive and
material
specifications
Azhar, 2011
CA Constructability assessment Visualisation of
construction
considerations or
variation assessment
before construction
commencement
results in cost and
time efficiency
Fadoul et al.,
2017
ME Measurement/estimation BIM offers accurate
quantity of materials
and estimation of
their total cost
Wu et al.,
2014
CD Clash detection BIM detects conflict
and interference by
combining the 3D
designs of structure,
architecture and
installation
Wang et al.,
2016
SC Sequence clarification Possibility of linking
planning and
scheduling via
supportive software
such as Navisworks
in a BIM package
clarifies project
sequence
Lee et al.,
2015
SMB Safety management Virtual site space and
automated available
Martinez-
Aires et al.,
1. Literature
review and gap
identification
3. Development of
observable variables
and data collection
tool
2. Hypothetical
model
4. Survey
conduction and
data collection
5. Data
analysis 6. Model
confirmation/revis
ion
Reliability
examination
Hypothetical tests
132
Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
safety measurements
provided by BIM
support safety
management at
construction sites
2018; Zhang
et al., 2013
PS Planning and scheduling Possibility to link
planning and
scheduling via
supportive software
in BIM packages
such as Navisworks
limits deviations and
ensures progress
Kiani et al.,
2015
SC Site coordination A virtual space
results in
optimisation of
construction activity
congestion and site
allocation
Azhar, 2011
OSM AP Automation and series
production
Centralisation of
construction activities
and series production
through automation
in a factory
environment may
reduce activity
congestion at the
construction site
Eastman &
Sacks, 2008;
Tibaut et al.,
2016
SM Safety management A centralised control
environment is safer
in OSM-based
projects
Pan et al.,
2012; SBEnrc,
2017
ST Sustainability Material and energy
usage are more
controllable (less
waste) in the factory
environment
Boyd et al.,
2013
FR Faster investment return OSM helps shorten
project completion
time
Elnaas et al.,
2009
WC Working conditions Labour costs are
cheaper and working
conditions more
comfortable in
factory environments
compared with
construction sites
Zhai, Reed, &
Mills, 2014
MKT Marketing Availability of
various volumetric
shapes of
Eastman &
Sacks, 2008
133
Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
prefabricated
elements better
support project
progress via OSM
compared with
traditional
construction
OSM–BIM I1SLM1 Sequence and location
management
BIM has the ability to
plan and link the
three processes of
design, production
and positioning of
OSM components
Sabet &
Chong, 2018;
Santos et al.,
2019
I1SLM2 BIM enables the best
components to be
stocked for later
dispatch by offering a
3D site space
Babič,
Podbreznik, &
Rebolj, 2010
I1SLM3 Component
dispatching is more
organised in a virtual
site space in OSM–
BIM-based projects
I2,3PS1 Planning and scheduling BIM supports
manufacturers by
addressing the exact
specifications of
components,
minimising errors
affecting project
progress
Utiome &
Drogemuller,
2013
I2,3PS2 BIM’s information
sharing and
communication
enables early
planning and
scheduling for
logistical issue of
manufactured
components in urban
sites for component
transfer through
timely decision-
making
Bortolini,
Formoso, &
Viana, 2019
I4SM1 Safety management BIM enables safer
movement and
transfer of
prefabricated
components by
providing shop
drawings of crane
Yeoh, Wong,
& Peng, 2016
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Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
operations on lifting
and moving loads and
virtual accessibility
of the relevant area
I4SM2 Virtual site
accessibility enables
safer component
dispatch (best route
for transferring)
because potentials for
collision are
identified
Shang & Shen,
2016
I4SM3 BIM recognises
potential falls in
OSM-based projects
because
manufactured units
may be large and
heavy
Zhang et al.,
2015
I5,6,7ST1 Sustainability Professional comfort
is achieved via
effective
communication in
OSM–BIM projects
Abanda et al.,
2017;
Juszczyk et
al., 2015
I5,6,7ST2 BIM can reduce or
minimise waste by
providing accurate
amounts of
construction
materials in OSM–
BIM projects
Liu et al.,
2011
I8IM1 Interface management BIM transfers paper-
based drawings of
prefabricated
components to a 3D
model that offers
quick access to
information for
stakeholders
Nath et al.,
2015
I8IM2 Required changes to
component
manufacture may be
quickly managed
among stakeholders
and actioned through
BIM’s information-
sharing platform
Woo, 2006
I9CC1 Contract condition In OSM–BIM
projects, the
responsibility for
mistakes or failure of
Chao-Duivis,
2011; Luth et
al., 2014
135
Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
contractual
obligations is easily
identified
I9CC2 Appropriate BIM
contractual
arrangements in an
OSM-based project
may prevent potential
disputes
Fan et al.,
2019
I10IT1 Information technology BIM promotes OSM
by identifying
repetition, resulting
in mass production in
manufacture
Sabet &
Chong, 2019
I10IT2 Building regulations
may be checked in
BIM models, and
manufacturers may
be notified of failure
in design before the
commencement of
physical work
Sabet &
Chong, 2019
I10IT3 BIM via 3D
modelling (greater
visualisation) enables
manufacturer to
better manage
information and
realise the required
specifications of
ordered parts
Tahir et al.,
2018;
Martinez et
al., 2019
I11VE1 Value engineering BIM enables the
systematic use of
OSM, increasing
predictability,
constructability and
efficiency and adding
value to projects
Jrade &
Lessard, 2015;
Abanda et al.,
2017
I11VE2 The capability of
visualisation in BIM
better enables cost
optimisation by
revealing the exact
quantity of alternative
materials
Yin et al.,
2019;
Gbadamosi et
al., 2018
I12CE Concurrent engineering Opportunities of fast-
tracking and
conducting activities
in parallel is better
supported in an
OSM–BIM-based
Farnsworth et
al., 2015;
Sabet &
Chong, 2019
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Latent variable Abbrev. Capabilities/
interactions
Observable
variables/indicators
Sources
contributing to
development
of
indicators
project, reflecting the
objectives of
concurrent
engineering
Project
performance
Quality BIM–OSM
interactions improve
project
Lee & Kim,
2017
Cost BIM–OSM
interactions reduce
project costs
Ocheoha &
Moselhi, 2018
Time BIM–OSM
interactions shorten
project duration
Arashpour et
al., 2018
Safety BIM–OSM
interactions improve
project
Abanda et al.,
2017
STS Stockholder satisfaction BIM–OSM
interactions improve
stakeholder
relationships and
satisfaction
Abanda et al.,
2017
6.5 Data Analysis and Findings
6.5.1 Data collection.
Australia was selected as the location of this research study. Construction
practitioners with relevant expertise were provided with a Qualtrics survey link. Paper
questionnaires were also distributed. The construction board of Engineers Australia,
social media (LinkedIn) and construction companies were contacted to network with
respondents. Respondents included construction managers, supervisors, project
engineers, site engineers, quantity surveyors and architects with academic or
professional experience of BIM and OSM. In total, 687 questionnaires were distributed,
77 of which were considered sufficiently valid to be included in the data analysis. A low
response rate is common in studies investigating the adoption of emerging techniques
and innovations in the construction industry (Ahankoob, Manley, Hon, & Drogemuller,
2018). An Australian research study by Ahankoob et al. (2018) focusing on BIM and
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the learning capacity of contractors was based on only 57 valid responses (12%
response rate). Ling (2003) conducted a survey on innovations in the construction field,
obtaining a response rate of only 6%. An effective method of motivating professionals
to participate is to contact a representative (i.e. one who represents a number of
practitioners) of institutions and companies. Representatives responded to the
questionnaire based on what they had observed in projects and following careful
reviews of project reports, contributing to the sufficiency and validity of the data.
Observable variables were evaluated by the respondents based on a 5-point
Likert scale. SEM was applied to analyse the respondents’ answers. As SEM requires
significant data, bootstrapping was also applied to increase the accuracy of the data
analysis.
6.5.2 Reliability of constructs.
Evaluation of the consistency and accuracy of the research instrument. An
instrument is considered accurate if it measures what it is intended to measure and
reliable if it produces the same results under the same conditions (Bolarinwa, 2015).
Cronbach’s alpha (with a coefficient of > 0.7) was used to evaluate the reliability of the
scales (Santos, 1999). Cronbach’s alpha for the questionnaire (0.94, as shown in Table
6.2) confirms its reliability.
Table 6.2 Reliability statistics
Cronbach’s alpha Cronbach’s alpha based on standardised items No. of items
0.941 0.942 38
Table 6.3 shows the factor loadings that represent an acceptable correlation
coefficient (> 0.3) for each observed variable. In other words, each variables
appropriately contributed to the suitability of questionnaire to measure what was
intended to be measured.
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Table 6.3 Measurement scale and properties of constructs
Construct Observed variable
(abbrev.)
Correlation coefficient
(factor loading)
Cronbach’s alpha
if item deleted
BIM 3D 0.46 0.94
CA 0.54 0.94
ME 0.54 0.94
CD 0.35 0.94
SC 0.53 0.94
SMB 0.61 0.94
PS 0.45 0.94
OSM SC 0.48 0.94
AP 0.48 0.94
SMO 0.48 0.94
STO 0.38 0.94
FR 0.36 0.94
WC 0.39 0.94
MKT 0.48 0.94
Interactions I1 SLM1 0.32 0.94
SLM2 0.58 0.94
SLM3 0.60 0.94
I2,3 PS1 0.46 0.94
PS2 0.58 0.94
I4 SM1 0.60 0.94
SM2 0.61 0.94
SM3 0.68 0.94
I5,6,7 ST1 0.49 0.94
ST2 0.76 0.94
I8 IM1 0.60 0.94
I9 CC1 0.65 0.94
CC2 0.46 0.94
I10 IT1 0.60 0.94
IT2 0.38 0.94
IT3 0.57 0.94
I11 VE1 0.47 0.94
VE2 0.46 0.94
I12 CE 0.61 0.94
Project performance Time 0.53 0.94
Cost 0.62 0.94
Quality 0.68 0.94
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Construct Observed variable
(abbrev.)
Correlation coefficient
(factor loading)
Cronbach’s alpha
if item deleted
Safety 0.65 0.94
Satisfaction 0.54 0.94
6.5.3 Hypothesis testing and interpretation.
SEM supported by bootstrapping was used to test the hypotheses. Standardised
path coefficient β was obtained from SEM using AMOS software. As Table 6.4 shows,
the p-values of the two first paths were greater than 0.05. This implies that, individually,
BIM and OSM did not significantly influence overall project performance. Therefore,
H1 and H2 are rejected. As can be seen in the third row, BIM significantly influenced
OSM was detected (β = 0.4, p < 0.05). Therefore, H3 is supported. Moreover, there was
a significant influence from both OSM (β = 0.79, p < 0.05) and BIM (β = 0.40, p <
0.05) on the interactions between OSM and BIM. This implies that each approach is
capable of interacting with the other. Therefore, H4 and H5 are supported. Finally, the
interaction between OSM and BIM significantly influenced overall project performance
(β = 0.86, p < 0.05). In the other words, the capabilities of each approach resulted in
constructive OSM–BIM interactions, improving the KPrIs contributing to the expected
project performance. Thus, H6 is supported.
Table 6.4 Hypothesis test results
Hypothesis Path Path
coefficient
(β)
p-
value
Interpretation
H1 Project performance < BIM 0.00 0.279 Not supported
H2 Project performance < OSM 0.49 0.175 Not supported
H3 OSM < BIM 0.31 0.003 Supported
H4 OSM–BIM interactions < OSM 0.79 0.015 Supported
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H5 OSM–BIM interactions < BIM 0.40 0.009 Supported
H6 Project performance < OSM–BIM
interactions
0.86 0.000 Supported
Figure 6.3 shows the path coefficients (regression weights) of the capabilities of
each approach and the interaction between OSM and BIM. For example, 3D BIM had a
weight of 0.68, OSM automation and series production had a weight of 1 and
concurrent engineering (I12CE) had a weight of 0.72. Based on these findings, OSM–
BIM interactions played a mediating role between BIM and OSM techniques in the
structural model of this research.
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Figure 6.3. SEM model
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6.6 Discussion and Contributions
Existing literature on BIM in OSM is limited. Goulding et al. (2012) claimed that BIM
can resolve fragmentation among designers, contractors, and manufacturers. Through a
qualitative research study, Vernikos et al. (2013) discovered that a OSM–BIM system
provides opportunities to improve interface management and configuration, access
information, and optimize procurement .They also claimed that it facilitates better
project contracts and more constructive managerial measures. Nawari et al. (2012)
established that a manufacturer—as a party in a project—could benefit from extracting
sufficient data from a BIM model. Ezcan et al. (2013) claimed that an enriched BIM
model can cover the weaknesses in an OSM-based project. Amanda et al. (2017)
reported that BIM in OSM-based projects provided more beneficial opportunities than
traditional construction projects. In addition, Liu et al. (2019) highlighted a range of
gaps, including the lack of a BIM generative system in OSM-based investigation. A
BIM-based system of design assessment and optimisation is necessary for linking the
design and assembly stages of a project (Ghadamosi et al., 2019). Ghadamosi et al.
(2019) integrated “the principles of Design for Manufacture and Assembly (DFMA) and
Lean Construction” (p. 1) to develop a BIM-based system.
This research measured the practicality of the individual capabilities of BIM and OSM
techniques and the practicality of their combined capabilities referred to OSM-BIM
interactions. To achieve this, SEM was used as a comprehensive method for clarifying
potential sophisticated relationships among the interconnected variables of this study. A
measurement instrument was developed to quantify the practicality of the two
techniques’ capabilities. Additionally, the measurement instrument provided
respondents with an opportunity to evaluate the capabilities of the techniques against
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their potential interactions. In other words, the respondents were provided with full
descriptions of capabilities and interactions to inform their judgment.
The first theoretical contribution is that interactions between OSM and BIM act as
mediators to improve KPrIs, which leads to overall project performance. This shows
that, when both approaches are systematically adopted, their capabilities reinforce
each other. These interactions have been addressed on how and which stages to be
applied throughout a project. Therefore, the interactions identified in this study have
practical implications for planning and management. For example, an enriched BIM
model clarifies any required technical specifications for building components with
high accuracy (Azhar, 2011). These specifications limit the chance of construction
errors. Meanwhile, OSM offers automation and series production, which significantly
contribute to a faster flow of progress (Eastman & Sacks, 2008; Tibaut et al., 2016).
This system has been identified as a capable solution to improve the affordability of
end users (Mostafa & Chileshe, 2018). In Australia, OSM adoption is one of the
pathways for construction industry improvement (Hu& Chong, 2019) and the role of
manufacturers contributing to an integrated project team has been highlighted (Hu&
Heap, 2020). Therefore, an OSM–BIM system can provide a construction project with
accurate technical specifications to accelerate the construction process. This is vital to
project performance in series production because rectifying errors in manufactured
components takes time and costs money, which can hinder projects. In an OSM–BIM-
based project, these capabilities can support interface management and satisfy
stakeholders. The interactions can also be clarified in terms of concurrent engineering,
which refers to fast-tracking the review and confirmation of the executive technical
requirements. This fast-tracking is made possible by developing virtual architectural,
structural, electrical, and mechanical models, rather than sequentially evaluating
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paper-based models. Therefore, the objective of concurrent engineering is fulfilled by
the opportunity of doing jobs in parallel (Farnsworth et al., 2015).
Innovation and the diffusion of innovation are the only ways to address future demand
in the construction industry (Lindblad & Guerrero, 2020). This research was grounded
in an interactive perspective, since it clarified three essential elements of innovation:
idea generation, opportunities, and diffusion (Gambatese et al., 2011). “Diffusion,” as
defined by Kale and Arditi (2010), is “the process by which an innovation is
communicated through certain channels over time among the members of a social
system” (p. 330). The concurrent application of OSM and BIM, in a hybrid system,
could allow the identified interactions to fulfil the objectives of both techniques. For
these reasons, the hybrid system represents an innovative process for overall project
performance, which can be widely applied in the industry. This application is in line
with diffusion innovation theory.
6.7 Conclusion
Both OSM and BIM have been identified as revolutionary techniques, capable of
addressing the issues threatening construction productivity. However, the uptake of OSM
and BIM varies from country to country. Gelic et al. (2016) highlighted Australia’s
limited uptake of BIM (Gelic et al. 2016) and Hosseini et al. (2018) argued for the
necessity of accelerating BIM’s maturity in Australia. Additionally, the extremely limited
success of OSM (Duc et al., 2014) and the lack of systematic progress from on-site
construction to OSM mean that the growth rate of OSM is lagging in comparison with
adoption trends in other pioneer countries that practice OSM (Khalfan & Maqsood, 2014).
The uncertain status of BIM may originate from its limited uptake in Australia (Gelic et
al., 2016) and its consequent immaturity in much of the Australian market (Hosseini et
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al., 2018). These issues may impede the effectiveness of the individual application of the
techniques and prevent BIM in OSM from moving beyond infancy in Australia.
This research study developed hypotheses and evaluated the relationships between BIM,
OSM, OSM–BIM interactions and overall project performance. To analyse the data and
test the hypotheses, SEM was used, supported by bootstrapping. As a professional format
of SEM, a hypothetical model and null hypotheses were developed. Regression and
correlation tests were applied to evaluate the hypotheses. A range of coefficients were
used to interpret the results. The findings show that there was no significant influences
from BIM and OSM on overall project performance when these techniques were applied
individually. Moreover, a significant influence from BIM on OSM was found, meaning
that the capabilities of the two techniques were interactive. Thus, a significant influence
from OSM–BIM interactions on overall project performance was hypothesised and
supported. By systematically adopting these techniques, interactions are capable of
boosting project performance via improving KPrIs. The current study revealed the degree
of the influence (regression weight) of each capability as well as direct and indirect
influences of the techniques on overall project performance (see Figure 6. 3). A
systematic adoption of these techniques has been addressed by developing their
interactions. These interactions are capable of optimizing dimensions of project
performance, namely time, cost, quality, safety, and stockholders’ satisfaction, by
improving KPrIs. As has been highlighted, productivity improvement is followed by
project performance.
Therefore, the output of this research may encourage clients and stakeholders to
embrace hybrid OSM–BIM-based projects to boost overall project performance.
Interactions should be implemented in the planning and managerial stages to boost
overall performance in the architecture, engineering and construction industry.
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Nevertheless, certain limitations need to be considered in this research. In this study, the
construction practitioners made professional judgments according to the current statuses
of OSM and BIM in Australia. Therefore, the conclusions of this research cannot be
generalised to other countries as a consequence of the small sample sizes and
subsequently limited data. However, some respondents represented a larger number of
respondents as they were the representatives of a company. Further research is needed
to reinforce the findings of these studies so that the construction industry would not
resistant the adoption of the hybrid OSM–BIM system.
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Chapter 7: Research Contributions
7.1 Introduction
This research study includes four articles, comprising Chapters 2 to 5. The
findings and contributions of each article have been discussed at the end of each
chapter. This chapter concludes the aim of the research, summarises how the objectives
were satisfied, flags the limitations and recommends further research.
7.2 The Satisfaction of Research Objectives and Research
Contributions
7.2.1 To identify productivity fundamentals and highlight the role of
advanced techniques for productivity improvement
The decline of construction productivity, which resulted in poorer project
performance, forced authorities to seek the root of this reduced productivity. The
reinvention of construction was deemed essential and the implementation of advanced
techniques has been observed as one of the solutions. However, it is clear that the
advanced techniques may not cover all the factors in productivity. Therefore, the first
step was to develop a range of productivity fundamentals. To pursue this objective, 128
academic publications were analysed. This objective was satisfied by developing six
measures at the concept and design levels, four measures at the contract and
procurement steps and four measures at the execution stage. Following this, the
pathway through which the commonly advanced techniques influenced the aspects of
project performance at the pre-construction and construction stages was clarified. From
there, construction professionals could understand how to optimise time, cost, quality,
safety and stakeholder satisfaction. Additionally, it is implicit that these advanced
techniques could be reinforced by productivity fundamentals. In other words, the
influences of the implementation of advanced techniques could be maximised by the
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company incorporating productivity fundamentals. This plan of study could also enable
technique developers to conceptualise the requirements of more influential techniques in
the future.
7.2.2 To investigate the current influential standalone capabilities of BIM
and OSM for a hybrid OSM–BIM conceptual framework
New concepts, such as OSM and BIM, have been revolutionary movements in
the construction industry. However, these methods have not yet fulfilled their full
potential in practice. These techniques could be independently applied in construction
projects, but their integrated application may contribute to the fulfilment of their full
potential and true benefits in the industry. Hence, a conceptual framework was required
to address a hybrid OSM–BIM system (HOBS). This objective has been satisfied
through a holistic understanding of the standalone capabilities of the two techniques. A
Scoping review was applied, and 47 academic publications were analysed to contribute
to the achievement of this objective. This research argued that BIM might effectively
improve OSM and that a range of potential interactions could be applied at the design
and construction stages. These potential interactions must be systematically adopted by
a collaboration of participants. From that informative discussion and overview, the idea
of BIM in OSM was well-formulated to bridge the capabilities of OSM and BIM. This
study provided a foundation for the development of the potential technical interactions
applicable in planning and managerial schemes. Overall, a well-formulated idea of BIM
in OSM, as well as a direction for further research, is the contribution of this effort.
7.2.3 To identify the potential interactions of BIM and OSM for improving
productivity
From a productivity perspective, KPrIs need to be improved for overall project
performance. These KPrIs have been targeted by the capabilities of advanced
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techniques. The objectives set out in BIM and OSM have been theoretically achieved,
but an argument has been made that the results may differ once they come into practice.
In other words, the existing relevant literature implies that the BIM and OSM
capabilities may influence a range of KPrIs that result in better project performance.
However, these objectives have not yet been fulfilled in practice. A hybrid concept was
raised, pairing BIM with OSM for overall project performance. BIM has been
hypothesised as having the potential to link design, manufacturing and construction.
Therefore, the first step was an in-depth investigation to identify the KPrIs. Second, the
development of potential interactions was required. Third, at which stage and how these
OSM–BIM interactions influence KPrIs was discussed. This objective was satisfied by
scanning 100 academic publications. A conceptual figure of KPrIs was generated and
12 systematically discovered OSM–BIM interactions were the output. This research
contributes to the body of knowledge concerning BIM in OSM by clarifying the
pathways of how potential OSM–BIM interactions influence KPrIs. The results of these
investigations can improve the planning and managerial stages, enabling productivity
improvement in OSM-based projects.
7.2.4 To determine the influences of the standalone capabilities of OSM and
BIM, as well as their interactions in project performance
The high demand for improvements in construction productivity has led to the
emergence of advanced techniques. These advanced techniques have been supposed to
optimise project performance via the improvement of KPrIs. It has been suggested that
the concurrent application of BIM and OSM, rather than the individual application of
these techniques, could enhance project performance. The research scope in this study
extended to Australia. The main output of this research revealed significant influences
from OSM–BIM interactions on overall project performance. This shows that by
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systematically adopting both techniques, their capabilities can reinforce each other.
These interactions were technically addressed where they were applicable. The second
theoretical contribution of this research is the diffusion of innovation theory because the
identified interactions support the concurrent adoption of OSM and BIM. These
interactions fulfil the objectives of both techniques in functional hybrid OSM–BIM
systems, which may be widely implemented in the construction industry.
These practical implications are notable because the applicability of interactions
in projects can be prescribed. Therefore, they can be a practical reference for the
practitioner in the planning and construction stages.
7.3 Overall Research Contributions
Apart from the four above-mentioned contributions, this research has uncovered
a range of constructive interactions that contribute to diffusion theories. The theories
and practices that paved the way for modern construction did so because they presented
strategic improvements to industry performance levels. The diffusion and
implementation of sustainable, modern construction practices require that technique
developers, policy makers and stakeholders share an innovative and interactive
perspective (the role of clients is disputed) (Gambatese & Hallowell, 2011; Zhang et al.,
2020). Holding this point of view to ‘influence the speed and direction of techniques
development and diffusion’ (Renz & Solas, 2016, p. 44) has been on the agenda at
government forums in both developing and developed countries. This research was
grounded in the interactive point of view, since it clarified three essential elements of
innovation: idea generation, opportunities and diffusion (Gambatese et al., 2011).
‘Diffusion’, as defined by Kale and Arditi (2010), is ‘the process by which an
innovation is communicated through certain channels over time among the members of
a social system’ (p. 330). Innovation and its diffusion are the only ways to address
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future demand in the construction industry (Lindblad & Guerrero, 2020). For these
reasons, the hybrid OSM–BIM system represents an innovative process for overall
project performance, which can be widely applied in the industry. This application is in
line with the diffusion innovation theory.
7.4 Conclusion
The construction industry has always suffered from poor productivity.
Construction productivity underlies project performance and, consequently, projects
have lagged below the expected level of performance. Advanced techniques have
emerged to address this issue, but they may not cover all the required areas of
construction productivity. More supportive fundamentals could reinforce the advanced
techniques for project performance. The concurrent application of some of these
techniques may generate constructive interactions that result in better overall project
performance. BIM and OSM, as advanced techniques, were bridged to eliminate poor
construction productivity and to enable overall project performance. This research
aimed to determine the influences of OSM–BIM interactions on overall project
performance. In this regard, first, an in-depth investigation was required to identify the
causes of poor productivity and the attempted solutions. To identify the required
productivity fundamentals and scan the advanced techniques and how they influenced
project performance, 128 academic publications were reviewed. By integrating these
findings, a conceptual framework was developed.
This research then focused on OSM and BIM techniques for a holistic
understanding of the two techniques. The idea of BIM in OSM was conceptualised by a
hybrid OSM–BIM framework, through the consultation of 47 academic papers. A
conceptual figure of key productivity indicators was developed to contribute to the
discussion on how the hybrid OSM–BIM system could improve construction
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productivity. Twelve potential interactions between OSM and BIM were the key output
of this effort, supported by 100 academic articles. The influences of OSM–BIM
interactions on overall project performance were empirically investigated through a data
collection from survey and data analysis via SEM (using AMOS software). The findings
showed that there were no significant influences from BIM and OSM on overall project
performance when these techniques were applied individually. Moreover, a significant
influence from BIM on OSM was found, meaning that the capabilities of the two
techniques were interactive. Thus, a significant influence from OSM–BIM interactions
on overall project performance was revealed.
7.5 Limitations, Recommendations and Future Research Directions
This research can be considered to have certain limitations. One is the lack of projects
within which both techniques were fully applied. The report detailing OSM–BIM-based
projects could represent a significant benchmark in theory and effectively support the
critical evaluation of the concept. The second limitation is the lack of professionals who
either had experience, or were academically familiar, with the two techniques. The third
is the lack of interest among the contractors and clients who were approached for this
study. The last limitation is the small data sample. In this study, the construction
practitioners made professional judgments according to the current statuses of OSM and
BIM in Australia. As data sample was small, the conclusions of this research cannot be
generalised to other countries.
Hence, the value of a hybrid OSM–BIM system should be brought to the
attention of companies, to facilitate a more collaborative environment for this
innovative research. Research discussing BIM in OSM is limited, but further research
could leverage the benefit of the hybrid system described in this study.
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The construction industry has been resistant to the systematic adoption of new
and advanced techniques, such as BIM and OSM, to fully enable their capabilities and
their interactions. This means that the partial application of these techniques may
interrupt their effectiveness.
Further studies from different perspectives may reveal the effectiveness of the
concurrent application of OSM and BIM. The perspective of a smart city could be one
viewpoint that accelerates the adoption of a hybrid OSM–BIM system in the
construction industry, which is resistant to change. This OSM–BIM system could be
referred to as smart construction. A smart city is regarded as a system with
interconnected sub-systems with complex social–economic interconnections. The
construction industry is one sub-system that plays a critical role in the global economy.
Modernised construction is recognised as a significant contributor to smart city
development. A modernised construction industry that offers more efficient services to
society’s users is also an inevitable part of delivering essential services and contributing
to quality of life. From a smart city perspective, OSM–BIM interactions could
contribute to the criteria of smart cities. In other words, the interactions can be found in
the objectives of sustainability and efficiency as the main themes of smart city
development. According to Albino et al. (2015) and Shapiro et al. (2006), the criteria of
the smart city can be divided into six categories. Figure 6.1 shows the categories that the
idea of smart construction can contain. A prospective study in this area, aligned with the
diffusion of innovation theory, could contribute to the field by promoting an integrative
industry viewpoint.
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Fig 7.1. Conceptual framework of smart construction for a smart city
7.6 Summary
This hybrid thesis included four academic papers, comprising Chapters 2 to 5, as
the foundations of its research. This chapter briefly reflected on these foundations,
articulating the research contributions, limitations, recommendations and future research
directions.
155
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202
Appendix A
Table A.1
Measurement of key constructs
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
Building
information
modelling
(BIM)
3D 3D modelling A detailed virtual
BIM offers
spatial, executive
and material
specifications
Azhar, 2011
CA Constructability
assessment
Visualisation of
construction
considerations or
variation
assessment before
construction
commencement
results in cost and
time efficiency
Fadoul et
al., 2017
ME Measurement/estimati
on
BIM offers
accurate quantity
of materials and
estimation of their
total cost
Wu et al.,
2014
CD Clash detection BIM detects
conflict and
interference by
combining the 3D
designs of
structure,
architecture and
installation
Wang et al.,
2016
SC Sequence clarification Possibility of
linking planning
and scheduling
via supportive
software such as
Navisworks in a
BIM package
Lee et al.,
2015
203
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
clarifies project
sequence
SMB Safety management Virtual site space
and automated
available safety
measurements
provided by BIM
support safety
management at
construction sites
Martinez-
Aires et al.,
2018;
Zhang et al.,
2013
PS Planning and
scheduling
Possibility to link
planning and
scheduling via
supportive
software in BIM
packages such as
Navisworks limits
deviations and
ensures progress
Kiani et al.,
2015
SC Site coordination A virtual space
results in
optimisation of
construction
activity
congestion and
site allocation
Azhar, 2011
Off-site
manufacturin
g (OSM)
AP Automation and series
production
Centralisation of
construction
activities and
series production
through
automation in a
factory
environment may
reduce activity
congestion at the
construction site
Eastman &
Sacks,
2008;
Tibaut et
al., 2016
SMO Safety management A centralised
control
environment is
Pan et al.,
2012;
SBEnrc,
2017
204
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
safer in OSM-
based projects
STO Sustainability Material and
energy usage are
more controllable
(less waste) in the
factory
environment
Boyd et al.,
2013
FR Faster investment
return
OSM helps
shorten project
completion time
Elnaas et
al., 2009
WC Working conditions Labour costs are
cheaper and
working
conditions more
comfortable in
factory
environments
compared with
construction sites
Zhai, Reed,
& Mills,
2014
MKT Marketing Availability of
various
volumetric shapes
of prefabricated
elements better
support project
progress via OSM
compared with
traditional
construction
Eastman &
Sacks, 2008
OSM–BIM I1SLM1 Sequence and location
management
BIM has the
ability to plan and
link the three
processes of
design,
production and
positioning of
OSM components
Sabet &
Chong,
2018;
Santos et
al., 2019
I1SLM2 BIM enables the
best components
to be stocked for
Babič,
Podbreznik,
205
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
later dispatch by
offering a 3D site
space
& Rebolj,
2010
I1SLM3 Component
dispatching is
more organised in
a virtual site
space in OSM–
BIM-based
projects
I2,3PS1 Planning and
scheduling
BIM supports
manufacturers by
addressing the
exact
specifications of
components,
minimising errors
affecting project
progress
Utiome &
Drogemulle
r, 2013
I2,3PS2 BIM’s
information
sharing and
communication
enables early
planning and
scheduling for
logistical issue of
manufactured
components in
urban sites for
component
transfer through
timely decision-
making
Bortolini,
Formoso, &
Viana, 2019
I4SM1 Safety management BIM enables safer
movement and
transfer of
prefabricated
components by
providing shop
drawings of crane
operations on
Yeoh,
Wong, &
Peng, 2016
206
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
lifting and
moving loads and
virtual
accessibility of
the relevant area
I4SM2 Virtual site
accessibility
enables safer
component
dispatch (best
route for
transferring)
because potentials
for collision are
identified
Shang &
Shen, 2016
I4SM3 BIM recognises
potential falls in
OSM-based
projects because
manufactured
units may be large
and heavy
Zhang et al.,
2015
I5,6,7ST
1
Sustainability Professional
comfort is
achieved via
effective
communication in
OSM–BIM
projects
Abanda et
al., 2017;
Juszczyk et
al., 2015
I5,6,7ST
2
BIM can reduce
or minimise waste
by providing
accurate amounts
of construction
materials in
OSM–BIM
projects
Liu et al.,
2011
I8IM1 Interface management BIM transfers
paper-based
drawings of
prefabricated
Nath et al.,
2015
207
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
components to a
3D model that
offers quick
access to
information for
stakeholders
I8IM2 Required changes
to component
manufacture may
be quickly
managed among
stakeholders and
actioned through
BIM’s
information-
sharing platform
Woo, 2006
I9CC1 Contract condition In OSM–BIM
projects, the
responsibility for
mistakes or
failure of
contractual
obligations is
easily identified
Chao-
Duivis,
2011; Luth
et al., 2014
I9CC2 Appropriate BIM
contractual
arrangements in
an OSM-based
project may
prevent potential
disputes
Fan et al.,
2019
I10IT1 Information
technology
BIM promotes
OSM by
identifying
repetition,
resulting in mass
production in
manufacture
Sabet &
Chong,
2019
I10IT2 Building
regulations may
be checked in
Sabet &
Chong,
2019
208
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
BIM models, and
manufacturers
may be notified of
failure in design
before the
commencement
of physical work
I10IT3 BIM via 3D
modelling
(greater
visualisation)
enables
manufacturer to
better manage
information and
realise the
required
specifications of
ordered parts
Tahir et al.,
2018;
Martinez et
al., 2019
I11VE1 Value engineering BIM enables the
systematic use of
OSM, increasing
predictability,
constructability
and efficiency
and adding value
to projects
Jrade &
Lessard,
2015;
Abanda et
al., 2017
I11VE2 The capability of
visualisation in
BIM better
enables cost
optimisation by
revealing the
exact quantity of
alternative
materials
Yin et al.,
2019;
Gbadamosi
et al., 2018
I12CE Concurrent
engineering
Opportunities of
fast-tracking and
conducting
activities in
parallel is better
supported in an
Farnsworth
et al., 2015;
Sabet &
Chong,
2019
209
Latent
variable
Abbrev. Capabilities/
interactions
Observable
variables/indicato
rs
Sources
contributing
to
developmen
t of
indicators
OSM–BIM-based
project, reflecting
the objectives of
concurrent
engineering
Project
performance
Quality BIM–OSM
interactions
improve project
Lee & Kim,
2017
Cost BIM–OSM
interactions
reduce project
costs
Ocheoha &
Moselhi,
2018
Time BIM–OSM
interactions
shorten project
duration
Arashpour
et al., 2018
Safety BIM–OSM
interactions
improve project
Abanda et
al., 2017
STS Stockholder
satisfaction
BIM–OSM
interactions
improve
stakeholder
relationships and
satisfaction
Abanda et
al., 2017
210
Appendix B
Permission from the Journal of Advances in Civil Engineering (Hindawi
publications)
From: Rennuel Gil Caguicla <[email protected]>
Sent: Tuesday, 7 April 2020 11:43 AM
To: Pejman Ghasemi Poor Sabet <[email protected]>
Subject: Re: Request for permission
Dear Dr. Ghasemi Poor Sabet,
Thank you for contacting Hindawi about your query.
All our journals are open access (http://about.hindawi.com/authors/open-access/), including
Advances in Civil Engineering. All articles are published under the Creative Commons Attribution
License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution,
and reproduction in any medium provided the original work is properly cited.
You are free to reuse this text, figure, table with proper citation and attribution of the Hindawi article
unless the text, figure, table is indicated to be from previously copyrighted work. In that case, you
should seek permission from the copyright holder of the original publication that included the text,
figure, table.
Please let me know if I can assist you with anything else.
Best regards,
Rennuel
211
Appendix C
Permission from the International Journal of Managing Projects in Business (Emerald
Publications)
From: Becky Taylor <[email protected]>
Sent: Tuesday, 7 April 2020 11:47 PM
To: Pejman Ghasemi Poor Sabet <[email protected]>
Subject: FW: FW: Request for permission
Dear Pejman Ghasemi Poor Sabet,
Many thanks for your email. Please allow me to introduce myself; my name is Becky Taylor
and I am a Rights Executive here at Emerald.
In answer to your question, Emerald allows its authors to include the published version of their
article within their written/printed thesis.
If your institution requires you to deposit an electronic copy of your thesis, then Emerald allows
its authors to place a non-Emerald-branded version of your article within the electronic version.
By non-branded, we mean that whilst it can have all of the editorial changes, it must be in a
different format, i.e. different font, different layout, etc., and must not have any Emerald logos
or branding. We also ask that you include the DOI of the article: https://doi.org/10.1108/IJMPB-
08-2018-0168
We request that the following statement appears on the first page of your reprinted article:
‘This article is © Emerald Publishing Limited and permission has been granted for this version
to appear here [please insert the web address here]. Emerald does not grant permission for this
article to be further copied/distributed or hosted elsewhere without the express permission from
Emerald Publishing Limited.’
For more information on what you can do with your work as an Emerald author, please refer to
our author rights
policy: http://www.emeraldgrouppublishing.com/authors/writing/author_rights.htm.
I hope this has answered your query, but please don’t hesitate to contact me if you have any
other questions.
I wish you the best of luck with your thesis.
Kind Regards,
Becky Taylor
Rights Executive I Emerald Publishing
I am currently working from home as Emerald’s UK offices are closed in response to the
Covid-19 pandemic. Our phone numbers are not being monitored.
212
Appendix D
Statement of Author’s Contributions
To Whom It May Concern
I, Pejman Ghasemi Poor Sabet, contributed abstract, introduction, poor
construction productivity, advanced techniques, review methodology, analysis and
findings, discussions, conclusions, recommendations and references significantly to the
paper/publication entitled “Pathways for the improvement of construction productivity:
A perspective on the adoption of advanced techniques.”
Pejman Ghasemi Poor Sabet
__ _______ (25/06/2020)
I, as a Co-Author, endorse that this level of contribution by the candidate
indicated above is appropriate.
Assoc. Prof Heap-Yih Chong
______ ______________________ (25/06/2020)
213
Appendix E
Statement of Author’s Contributions
To Whom It May Concern
I, Pejman Ghasemi Poor Sabet, contributed abstract, introduction, the
application of BIM and OSM techniques, review methodology, discussion on the
formulation of BIM in OSM conclusions and references significantly to the paper
entitled “A conceptual hybrid OSM–BIM framework to improve construction project
performance.”
Pejman Ghasemi Poor Sabet
__ ___________________(25/06/2020)
I, as a Co-Author, endorse that this level of contribution by the candidate
indicated above is appropriate.
Assoc. Prof Heap-Yih Chong
____________ _______________(25/06/2020)
214
Appendix F
Statement of Author’s Contributions
To Whom It May Concern
I, Pejman Ghasemi Poor Sabet, contributed abstract, introduction, literature
review on the key productivity indicators, findings on BIM and OSM for the
interactions between them, review methodology, analysis and discussion of the
improvements of KPrIs via the the OSM and BIM capabilities and the interactions as
well as their influences on the overall project performance, conclusions and references
significantly to the paper/publication entitled “ Interactions between building
information modelling and off-site manufacturing for productivity improvement”
Pejman Ghasemi Poor Sabet
(25/06/2020)
I, as a Co-Author, endorse that this level of contribution by the candidate
indicated above is appropriate.
Assoc. Prof Heap-Yih Chong
__________ ________________(25/06/2020)
215
Appendix G
Statement of Author’s Contributions
To Whom It May Concern
I, Pejman Ghasemi Poor Sabet, contributed abstract, introduction, literature
review, methodology, empirical evaluation the impact of standalone BIM and OSM
capabilities and their interactions via KPrIs, SEM application, discussion on overall
project performance, conclusions and references significantly to the paper/publication
entitled “Appraisal of potential interactions between building information modelling
and off-site manufacturing for overall project performance.”
Pejman Ghasemi poor Sabet
_ _____________________ (25/06/2020)
I, as a Co-Author, endorse that this level of contribution by the candidate
indicated above is appropriate.
Assoc. Prof Heap-Yih Chong
_________ _________________ (25/06/2020)
Dr Chamila Ramanayaka
Appendix HDear Sir/Madam,Welcome to the survey.You are invited as a construction practitioner to participate in this research. The research aims to discuss how Building Information Modelling (BIM) and Off-site Manufacturing (OSM), as well as their potential interactions, are capable of improving performance/productivity.The following explanations are provided for respondents to briefly clarify what are BIM and OSM referred to in this research. this survey takes about 15 mins of your time.
The following explanations are provided for respondents to briefly clarify what are BIM and OSM referred to in this research.- BIM is the process of developing and applying a simulated model of designing, planning,construction and operation of a building. The model contains a collection of digital data and richinformation about all details related to a project during its life cycle. The BIM model originatedfrom a smart 3-dimensional CAD which is automatically adaptable to any change and isconnected to a shareable database performing as a common source among the parties involvedin a project.- OSM is a modern technique in which off-site constructed components are produced andattached to on-site activities. In fact, the off-site components are produced in a controllingmanufacture environment and then transported to and positioned into a construction site.
Your efforts and time are highly appreciable for answering the questionnaire below.
STATEMENT BY PERSON AGREEING TO PARTICIPATE IN THIS STUDY.I have read the informed consent document and the material contained in it has been explained to me virtually. I understand each part of the document, all my questions have been answered and I freely and voluntarily choose to participate in this study.
Yes II consentt
No II do nott consentt
Q2.How do you know BIM?
Onlyly fromf academicic studiesti
1-3 years’’ experiencei
3-5 years’’ experiencei
Over 5 years’’ experiencei
Q3. How do you know OSM?
Onlyly fromf academicic studiesti
1-3 years’’ experiencei
3-5 years’’ experiencei
Over 5 years’’ experiencei
Q4.Pleasel selectlt an answer forf thet questionsti belowl based on your knowledgel and experiencei inin OSM and BIMIM practicesti by referringfi toto thet scalesl offStronglytly disagree=SD,i, Disagree=D,i, Neutraltl =N,, Stronglytly agree=SA,, and Agree=A..
Neither agree norStrongly agree Agree disagree Disagree Strongly disagree
II observe thattt centralizationtliti offthet constructiontti activitiestiiti intoito afactoryft environmentit couldld reduceactivitiestiiti congestionti ininconstructiontti siteite thattt resultlt inin abettertt constructiontti siteite controltl..
II observe thattt OSM helpsl ininshorteningti projectjt completionltitimeti..
II observe thattt a cheaper labourlcostt inin a factoryft environmentitcompared toto thet workerspaymentt ratete inin a constructionttisiteite..
II observe thattt materialtil usage isismore controllabletllle (lessl waste)t ininthet factoryft environmentit thatttresultslts inin a bettertt productivitytiity..
II observe thattt a centralizedtlicontrollingtlli environmentit isis saferf ininOSM-based projectsjts..
II observe thattt differentifft andvolumetricltic shapes off thetelementslts can be appliedli ininstructural,ttl, architecturalittl andinstallationitllti (mechanicalil andelectrical)ltil) designsi..
II observe thattt a bettertt projectjtprogress isis achievableile throught aBIMIM modell thattt offersff accuratetequantitytity off materialstils andestimationtiti off theirtir totalttl costt..
II observe thattt a bettertt projectjtprogress isis achievableile throught aBIMIM modell thattt offersff moreaccuratete estimationtiti off theirtir totalttlcostt..
II observe thattt a higheriproductivitytiity ratete can be resultedltby planningli softwareft availableille forfa BIMIM model,l, such as Navisworki4D,, etctc..II observe thattt BIMIM modell limitsliitschance off any deviationsiti duringiconstructiontti staget thattt improvesithet projectjt progress..II observe thattt thet visualizationiliti offconstructiontti considerationsiti orvariationiti assessmentt beforefactualtl constructiontticommencementt throught BIMIMcouldld resultlt inin costt and timetiefficiencyffii..II observe thattt BIMIM offersff chancestoto detecttt any conflictflit andinterferenceitf by combiningii thet 3-D designsi off structure,tt,architecture,itt, and installationsitllti..
II observe thattt siteite coordinationitithrought a virtualitl space resultslts ininoptimizationtiiti off constructionttiactivitiestiiti..II observe thattt BIMIM modell has thetabilityility toto planl and linkli thet threetprocesses includingili design,i,production,ti, and positioningitii offOSM componentsts..II observe thattt BIMIM promotest thetpaper-based drawingsi offcomponentsts toto a 3-D modell thatttoffersff allll informationifti.. Thisis pointitcauses a quickeri leadl timeti ininOSM-based projectsjts..II observe thattt BIMIM enablesl thetbestt componentsts stockt forf laterltdispatchit viaia offeringffi a 3D siteitespace or supplyly-chaininmanagementt..
II observe thattt BIMIM supportstsmanufacturersft by addressingi thetexactt specificationsifiti minimizingiiiierrors thattt affectfft projectjt progress..
II observe thattt componenttdispatchingiti isis toto be moreorganizedi viaia a virtualitl siteite spaceinin an OSM-BIMIM-based projectjt..
II observe thattt BIM’sI’ informationiftisharingi and communicationitienablesl earlyly planningli andschedulingli forf logisticsliti issuei offmanufacturedft componentsts ininurban sitesit forf components’t’transfertf throught timelytily decisionii-makingi (thet bestt date,t, timeti androute)t..II observe thattt BIMIM enablesl saferfmovementt and transfertf off thetcomponentsts by providingii shopdrawingsi forf crane operationti onhow liftinglifti and movingi thet loadsland virtualitl accessibilityiility off thetrelevantlt area..
II observe thattt Virtualitl siteiteaccessibilityiility wouldld enablele saferfcomponentt dispatchit (bestt routeteforf transferring)tfi sincei anypotentialttil off collisionllii wouldld benotifiedtifi..II observe thattt thattt BIMIM wouldldrecognizei potentialttil fallingflli failuresfilinin an OSM-based projectjt sinceithet manufacturedft unitit may beheavy and huge..
II observe thattt thattt BIMIM canreduce or minimizeiii thet wastete byprovidingii thet accuratete amountt offthet constructiontti materialtil inin anOSM-BIMIM projectjt..
II observe thattt a professionalfilcomfortft isis achievedi viaia aneffectiveffti communicationiti inin anOSM-BIMIM projectjt..
II observe thattt any requiredichanges on thet componentt totomanufactureft wouldld be quicklyilymanaged among thetstockholderstl and actionedtithrought BIM’sI’ informationifti sharingiplatformltf..
II observe thattt an appropriateite BIMIMcontractualttl arrangementt inin anOSM-based projectjt couldld preventtthet potentialttil disputesit..
II observe thattt inin OSM-BIMIMprojects,jt, thet responsibleile sidei forfany mistakesit or any failurefil offcontractualttl obligationsliti are easilyilyidentifieditifi and tracedt..
II observe thattt BIMIM promotestOSM viaia identifyingitifi repetitiontitiresultinglti inin mass productionti ininmanufactureft..II observe thattt buildingili regulationslticouldld be checked inin a BIMIM modelland any failurefil inin designi can benotifiedtifi toto manufacturerft beforefcommencementt any physicalilworks..II observe thattt BIMIM viaia 3D modell(greatert visualization)iliti enableslmanufacturerft toto realizeli thetrequiredi specificationsifiti off thetordered partsts..
II observe thattt BIMIM enablesl asystematicttic use off OSM andincreasesi predictabilityitility andconstructabilityttility,, and efficiencyffiithattt resultlt inin addingi valuel on thetprojectjt..
II observe thattt thet capabilityility offvisualizationiliti inin BIMIM betterttenablesl costt optimizationtiiti throughtrevealingli thet exactt quantitytity off thetalternativeltti materialstils..II observe thattt thet opportunitiestiti offfastft-trackingti and doingi someactivitiestiiti inin parallellll wouldld bebettertt supportedt inin an OSM-BIMIM-based projectsjts thattt reflectflt thetobjectivesjti off concurrenttengineeringii..II observe thattt thet BIMIM and OSMinteractionsitti have improvedi thetqualitylity off thet projectjt..II observe thattt thet outcomet off thetBIMIM and OSM interactionsitti havereduced thet costt off thet projectjt..II observe thattt thet BIMIM and OSMinteractionsitti have shortenedt thetdurationti off thet projectjt..II observe thattt thet BIMIM and OSMinteractionsitti have improvedi thetsafetyfty aspectsts off thet projectjt..II observe thattt thet BIMIM and OSMinteractionsitti have improvedistakeholders’tl’ relationshipltiip andsatisfactiontifti towardt a perfectftprojectjt progress..
Q6. You are very welcomedl toto recommend any othert potentialttil interactionitti thattt can be developedl among OSM and BIMIM and be implementedilt ininthet project’sjt’ stagest toto improvei productivitytiity..
There is always the known knows, that of human interface with such system, currently that would always be known to cause some percentage of risk with human interaction, further the system is only as good as the value of truth entered into said system, reduce the channels.of input and try to have 1 source of truth and entry, review, challenge and change accordingly
Q7. Please leave your e-mail address if you would be happy to participate in the next round of the research as well.
Location Data
Location: (-31.967407226562, 115.86209106445)
Source: GeoIP Estimation
